ICCV2021-Papers-with-Code

ICCV 2021 论文和开源项目合集(papers with code)！

1617 papers accepted - 25.9% acceptance rate

ICCV 2021 收录论文IDs：https://docs.google.com/spreadsheets/u/1/d/e/2PACX-1vRfaTmsNweuaA0Gjyu58H_Cx56pGwFhcTYII0u1pg0U7MbhlgY0R6Y-BbK3xFhAiwGZ26u3TAtN5MnS/pubhtml

注1：欢迎各位大佬提交issue，分享ICCV 2021论文和开源项目！

注2：关于往年CV顶会论文以及其他优质CV论文和大盘点，详见： https://github.com/amusi/daily-paper-computer-vision

【ICCV 2021 论文和开源目录】

Backbone
Transformer
涨点神器
GAN
NAS
NeRF
Loss
Zero-Shot Learning
Few-Shot Learning
长尾(Long-tailed)
Vision and Language
无监督/自监督(Self-Supervised)
Multi-Label Image Recognition(多标签图像识别)
2D目标检测(Object Detection)
语义分割(Semantic Segmentation)
实例分割(Instance Segmentation)
医学图像分割(Medical Image Segmentation)
视频目标分割(Video Object Segmentation)
Few-shot Segmentation
人体运动分割(Human Motion Segmentation)
目标跟踪(Object Tracking)
3D Point Cloud
3D Object Detection(3D目标检测)
3D Semantic Segmenation(3D语义分割)
3D Instance Segmentation(3D实例分割)
3D Multi-Object Tracking(3D多目标跟踪)
Point Cloud Denoising(点云去噪)
Point Cloud Registration(点云配准)
Point Cloud Completion(点云补全)
雷达语义分割(Radar Semantic Segmentation)
图像恢复(Image Restoration)
超分辨率(Super-Resolution)
去噪(Denoising)
医学图像去噪(Medical Image Denoising)
去模糊(Deblurring)
阴影去除(Shadow Removal)
视频插帧(Video Frame Interpolation)
视频修复/补全(Video Inpainting)
行人重识别(Person Re-identification)
行人搜索(Person Search)
2D/3D人体姿态估计(2D/3D Human Pose Estimation)
6D位姿估计(6D Object Pose Estimation)
3D人头重建(3D Head Reconstruction)
人脸识别(Face Recognition)
人脸表情识别(Facial Expression Recognition)
行为识别(Action Recognition)
时序动作定位(Temporal Action Localization)
动作检测(Action Detection)
群体活动识别(Group Activity Recognition)
手语识别(Sign Language Recognition)
文本检测(Text Detection)
文本识别(Text Recognition)
文本替换(Text Repalcement)
视觉问答(Visual Question Answering, VQA)
对抗攻击(Adversarial Attack)
深度估计(Depth Estimation)
视线估计(Gaze Estimation)
人群计数(Crowd Counting)
车道线检测(Lane Detection)
轨迹预测(Trajectory Prediction)
异常检测(Anomaly Detection)
场景图生成(Scene Graph Generation)
图像编辑(Image Editing)
图像合成(Image Synthesis)
图像检索(Image Retrieval)
三维重建(3D Reconstruction)
视频稳像(Video Stabilization)
细粒度识别(Fine-Grained Recognition)
风格迁移(Style Transfer)
神经绘画(Neural Painting)
特征匹配(Feature Matching)
语义对应(Semantic Correspondence)
边缘检测(Edge Detection)
相机标定(Camera Calibration)
图像质量评估(Image Quality Assessment)
度量学习(Metric Learning)
Unsupervised Domain Adaptation
Video Rescaling
Hand-Object Interaction
Vision-and-Language Navigation
数据集(Datasets)
其他(Others)

Backbone

Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

Paper(Oral): https://arxiv.org/abs/2102.12122
Code: https://github.com/whai362/PVT

AutoFormer: Searching Transformers for Visual Recognition

Paper: https://arxiv.org/abs/2107.00651
Code: https://github.com/microsoft/AutoML

Bias Loss for Mobile Neural Networks

Paper: https://arxiv.org/abs/2107.11170
Code: None

Vision Transformer with Progressive Sampling

Paper: https://arxiv.org/abs/2108.01684
Code: https://github.com/yuexy/PS-ViT

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Paper: https://arxiv.org/abs/2101.11986
Code: https://github.com/yitu-opensource/T2T-ViT

Rethinking Spatial Dimensions of Vision Transformers

Paper: https://arxiv.org/abs/2103.16302
Code: https://github.com/naver-ai/pit

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Paper: https://arxiv.org/abs/2103.14030
Code: https://github.com/microsoft/Swin-Transformer

Conformer: Local Features Coupling Global Representations for Visual Recognition

Paper: https://arxiv.org/abs/2105.03889
Code: https://github.com/pengzhiliang/Conformer

MicroNet: Improving Image Recognition with Extremely Low FLOPs

Paper: https://arxiv.org/abs/2108.05894
Code: https://github.com/liyunsheng13/micronet

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Paper: https://arxiv.org/abs/2102.01063
Code: https://github.com/idstcv/ZenNAS

Visual Transformer

Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

Paper: https://arxiv.org/abs/2103.14030
Code: https://github.com/microsoft/Swin-Transformer

An Empirical Study of Training Self-Supervised Vision Transformers

Paper(Oral): https://arxiv.org/abs/2104.02057
MoCo v3 Code: None

Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions

Paper(Oral): https://arxiv.org/abs/2102.12122
Code: https://github.com/whai362/PVT

Group-Free 3D Object Detection via Transformers

Paper: https://arxiv.org/abs/2104.00678
Code: None

Spatial-Temporal Transformer for Dynamic Scene Graph Generation

Paper: https://arxiv.org/abs/2107.12309
Code: None

Rethinking and Improving Relative Position Encoding for Vision Transformer

Paper: https://arxiv.org/abs/2107.14222
Code: https://github.com/microsoft/AutoML/tree/main/iRPE

Emerging Properties in Self-Supervised Vision Transformers

Paper: https://arxiv.org/abs/2104.14294
Code: https://github.com/facebookresearch/dino

Learning Spatio-Temporal Transformer for Visual Tracking

Paper: https://arxiv.org/abs/2103.17154
Code: https://github.com/researchmm/Stark

Fast Convergence of DETR with Spatially Modulated Co-Attention

Paper: https://arxiv.org/abs/2101.07448
Code: https://github.com/abc403/SMCA-replication

Vision Transformer with Progressive Sampling

Paper: https://arxiv.org/abs/2108.01684
Code: https://github.com/yuexy/PS-ViT

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

Paper: https://arxiv.org/abs/2101.11986
Code: https://github.com/yitu-opensource/T2T-ViT

Rethinking Spatial Dimensions of Vision Transformers

Paper: https://arxiv.org/abs/2103.16302
Code: https://github.com/naver-ai/pit

The Right to Talk: An Audio-Visual Transformer Approach

Paper: https://arxiv.org/abs/2108.03256
Code: None

Joint Inductive and Transductive Learning for Video Object Segmentation

Paper: https://arxiv.org/abs/2108.03679
Code: https://github.com/maoyunyao/JOINT

Conformer: Local Features Coupling Global Representations for Visual Recognition

Paper: https://arxiv.org/abs/2105.03889
Code: https://github.com/pengzhiliang/Conformer

Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer

Paper: https://arxiv.org/abs/2108.03032
Code: https://github.com/zhiheLu/CWT-for-FSS

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction

Paper: https://arxiv.org/abs/2108.03798
Code: https://github.com/wzmsltw/PaintTransformer

Conditional DETR for Fast Training Convergence

Paper: https://arxiv.org/abs/2108.06152
Code: https://github.com/Atten4Vis/ConditionalDETR

MUSIQ: Multi-scale Image Quality Transformer

Paper: https://arxiv.org/abs/2108.05997
Code: https://github.com/google-research/google-research/tree/master/musiq

SOTR: Segmenting Objects with Transformers

Paper: https://arxiv.org/abs/2108.06747
Code: https://github.com/easton-cau/SOTR

PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

Paper(Oral): https://arxiv.org/abs/2108.08839
Code: https://github.com/yuxumin/PoinTr

SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

Paper: https://arxiv.org/abs/2108.04444
Code: https://github.com/AllenXiangX/SnowflakeNet

Improving 3D Object Detection with Channel-wise Transformer

Paper: https://arxiv.org/abs/2108.10723
Code: https://github.com/hlsheng1/CT3D

TransFER: Learning Relation-aware Facial Expression Representations with Transformers

Paper: https://arxiv.org/abs/2108.11116
Code: None

GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer

Paper: https://arxiv.org/abs/2108.12630
Code: https://github.com/xueyee/GroupFormer

Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction

Paper: https://arxiv.org/abs/2109.00512
Code: https://github.com/facebookresearch/co3d
Dataset: https://github.com/facebookresearch/co3d

Voxel Transformer for 3D Object Detection

Paper: https://arxiv.org/abs/2109.02497
Code: None

3D Human Texture Estimation from a Single Image with Transformers

Homepage: https://www.mmlab-ntu.com/project/texformer/
Paper(Oral): https://arxiv.org/abs/2109.02563
Code: None

FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting

Paper: https://arxiv.org/abs/2109.02974
Code: https://github.com/ruiliu-ai/FuseFormer

CTRL-C: Camera calibration TRansformer with Line-Classification

Paper: https://arxiv.org/abs/2109.02259
Code: https://github.com/jwlee-vcl/CTRL-C

An End-to-End Transformer Model for 3D Object Detection

Homepage: https://facebookresearch.github.io/3detr/
Paper: https://arxiv.org/abs/2109.08141
Code: https://github.com/facebookresearch/3detr

Eformer: Edge Enhancement based Transformer for Medical Image Denoising

Paper: https://arxiv.org/abs/2109.08044
Code: None

PnP-DETR: Towards Efficient Visual Analysis with Transformers

Paper: https://arxiv.org/abs/2109.07036
Code: https://github.com/twangnh/pnp-detr

Transformer-based Dual Relation Graph for Multi-label Image Recognition

Paper: https://arxiv.org/abs/2110.04722
Code: None

涨点神器

FaPN: Feature-aligned Pyramid Network for Dense Image Prediction

Paper: https://github.com/EMI-Group/FaPN
Code: https://arxiv.org/abs/2108.07058

Unifying Nonlocal Blocks for Neural Networks

Paper: https://arxiv.org/abs/2108.02451
Code: https://github.com/zh460045050/SNL_ICCV2021

Towards Learning Spatially Discriminative Feature Representations

Paper: https://arxiv.org/abs/2109.01359
Code: None

GAN

Labels4Free: Unsupervised Segmentation using StyleGAN

Homepage: https://rameenabdal.github.io/Labels4Free/
Paper: https://arxiv.org/abs/2103.14968

GNeRF: GAN-based Neural Radiance Field without Posed Camera

Paper(Oral): https://arxiv.org/abs/2103.15606
Code: https://github.com/MQ66/gnerf

EigenGAN: Layer-Wise Eigen-Learning for GANs

Paper: https://arxiv.org/abs/2104.12476
Code: https://github.com/LynnHo/EigenGAN-Tensorflow

From Continuity to Editability: Inverting GANs with Consecutive Images

Paper: https://arxiv.org/abs/2107.13812
Code: https://github.com/Qingyang-Xu/InvertingGANs_with_ConsecutiveImgs

Sketch Your Own GAN

Homepage: https://peterwang512.github.io/GANSketching/
Paper: https://arxiv.org/abs/2108.02774
代码: https://github.com/peterwang512/GANSketching

Manifold Matching via Deep Metric Learning for Generative Modeling

Paper: https://arxiv.org/abs/2106.10777
Code: https://github.com/dzld00/pytorch-manifold-matching

Dual Projection Generative Adversarial Networks for Conditional Image Generation

Paper: https://arxiv.org/abs/2108.09016
Code: None

GAN Inversion for Out-of-Range Images with Geometric Transformations

Paper: https://arxiv.org/abs/2108.08998
Code: None

ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement

Homepage: https://yuval-alaluf.github.io/restyle-encoder/
Paper: https://arxiv.org/abs/2104.02699
Code: https://github.com/yuval-alaluf/restyle-encoder

StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery

Paper(Oral): https://arxiv.org/abs/2103.17249
Code: https://github.com/orpatashnik/StyleCLIP

Image Synthesis via Semantic Composition

Homepage: https://shepnerd.github.io/scg/
Paper: https://arxiv.org/abs/2109.07053
Code: https://github.com/dvlab-research/SCGAN

NAS

AutoFormer: Searching Transformers for Visual Recognition

Paper: https://arxiv.org/abs/2107.00651
Code: https://github.com/microsoft/AutoML

BN-NAS: Neural Architecture Search with Batch Normalization

Paper: https://arxiv.org/abs/2108.07375
Code: https://github.com/bychen515/BNNAS

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Paper: https://arxiv.org/abs/2102.01063
Code: https://github.com/idstcv/ZenNAS

NeRF

GNeRF: GAN-based Neural Radiance Field without Posed Camera

Paper(Oral): https://arxiv.org/abs/2103.15606
Code: https://github.com/MQ66/gnerf

KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs

Paper: https://arxiv.org/abs/2103.13744
Code: https://github.com/creiser/kilonerf

In-Place Scene Labelling and Understanding with Implicit Scene Representation

Homepage: https://shuaifengzhi.com/Semantic-NeRF/
Paper(Oral): https://arxiv.org/abs/2103.15875

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis

Homepage: https://ajayj.com/dietnerf
Paper(DietNeRF): https://arxiv.org/abs/2104.00677

BARF: Bundle-Adjusting Neural Radiance Fields

Homepage: https://chenhsuanlin.bitbucket.io/bundle-adjusting-NeRF/
Paper(Oral): https://arxiv.org/abs/2104.06405
Code: https://github.com/chenhsuanlin/bundle-adjusting-NeRF

Self-Calibrating Neural Radiance Fields

Paper: https://arxiv.org/abs/2108.13826
Code: https://github.com/POSTECH-CVLab/SCNeRF

Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction

Paper: https://arxiv.org/abs/2109.00512
Code: https://github.com/facebookresearch/co3d
Dataset: https://github.com/facebookresearch/co3d

Neural Articulated Radiance Field

Paper: https://arxiv.org/abs/2104.03110
Code: https://github.com/nogu-atsu/NARF

NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo

Paper(Oral): https://arxiv.org/abs/2109.01129
Code: https://github.com/weiyithu/NerfingMVS

SNARF: Differentiable Forward Skinning for Animating Non-rigid Neural Implicit Shapes

Homepage: https://xuchen-ethz.github.io/snarf
Paper: https://arxiv.org/abs/2104.03953
Code: https://github.com/xuchen-ethz/snarf

CodeNeRF: Disentangled Neural Radiance Fields for Object Categories

Paper: https://arxiv.org/abs/2109.01750
Code: https://github.com/wayne1123/code-nerf

PIRenderer: Controllable Portrait Image Generation via Semantic Neural Rendering

Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Ren_PIRenderer_Controllable_Portrait_Image_Generation_via_Semantic_Neural_Rendering_ICCV_2021_paper.html
Code: https://github.com/RenYurui/PIRender

Loss

Rank & Sort Loss for Object Detection and Instance Segmentation

Paper(Oral): https://arxiv.org/abs/2107.11669
Code: https://github.com/kemaloksuz/RankSortLoss

Bias Loss for Mobile Neural Networks

Paper: https://arxiv.org/abs/2107.11170
Code: None

A Robust Loss for Point Cloud Registration

Paper: https://arxiv.org/abs/2108.11682
Code: None

Reconcile Prediction Consistency for Balanced Object Detection

Paper: https://arxiv.org/abs/2108.10809
Code: None

Influence-Balanced Loss for Imbalanced Visual Classification

Paper: https://arxiv.org/abs/2110.02444
Code: https://github.com/pseulki/IB-Loss

Zero-Shot Learning

FREE: Feature Refinement for Generalized Zero-Shot Learning

Paper: https://arxiv.org/abs/2107.13807
Code: https://github.com/shiming-chen/FREE

Discriminative Region-based Multi-Label Zero-Shot Learning

Paper: https://arxiv.org/abs/2108.09301
Code: https://arxiv.org/abs/2108.09301

Semantics Disentangling for Generalized Zero-Shot Learning

Paper: https://arxiv.org/pdf/2101.07978
Code: https://github.com/uqzhichen/SDGZSL

Few-Shot Learning

Relational Embedding for Few-Shot Classification

Paper: https://arxiv.org/abs/2108.0966
Code: https://github.com/dahyun-kang/renet

Few-Shot and Continual Learning with Attentive Independent Mechanisms

Paper: https://arxiv.org/abs/2107.14053
Code: https://github.com/huang50213/AIM-Fewshot-Continual

Few Shot Visual Relationship Co-Localization

Homepage: https://vl2g.github.io/projects/vrc/
Paper: https://arxiv.org/abs/2108.11618

长尾(Long-tailed)

Parametric Contrastive Learning

Paper: https://arxiv.org/abs/2107.12028
Code: https://github.com/jiequancui/Parametric-Contrastive-Learning

Influence-Balanced Loss for Imbalanced Visual Classification

Paper: https://arxiv.org/abs/2110.02444
Code: https://github.com/pseulki/IB-Loss

Vision and Language

VLGrammar: Grounded Grammar Induction of Vision and Language

Paper: https://arxiv.org/abs/2103.12975
Code: https://github.com/evelinehong/VLGrammar

无监督/自监督(Un/Self-Supervised)

An Empirical Study of Training Self-Supervised Vision Transformers

Paper(Oral): https://arxiv.org/abs/2104.02057
MoCo v3 Code: None

DetCo: Unsupervised Contrastive Learning for Object Detection

Paper: https://arxiv.org/abs/2102.04803
Code: https://github.com/xieenze/DetCo

Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization

Paper: https://arxiv.org/abs/2108.02183
Code: None

Improving Contrastive Learning by Visualizing Feature Transformation

Paper(Oral): https://arxiv.org/abs/2108.02982
Code: https://github.com/DTennant/CL-Visualizing-Feature-Transformation

Self-Supervised Visual Representations Learning by Contrastive Mask Prediction

Paper: https://arxiv.org/abs/2108.08012
Code: None

Temporal Knowledge Consistency for Unsupervised Visual Representation Learning

Paper: https://arxiv.org/abs/2108.10668
Code: None

MultiSiam: Self-supervised Multi-instance Siamese Representation Learning for Autonomous Driving

Paper: https://arxiv.org/abs/2108.12178
Code: https://github.com/KaiChen1998/MultiSiam

Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds

Homepage: https://siyuanhuang.com/STRL/
Paper: https://arxiv.org/abs/2109.00179
Code: https://github.com/yichen928/STRL

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval

Paper: https://arxiv.org/abs/2109.02244
Code: https://github.com/youngkyunJang/SPQ

Self-Supervised Representation Learning from Flow Equivariance

Paper: https://arxiv.org/abs/2101.06553
Code: None

Multi-Label Image Recognition(多标签图像识别)

Residual Attention: A Simple but Effective Method for Multi-Label Recognition

Paper: https://arxiv.org/abs/2108.02456
Code: https://github.com/Kevinz-code/CSRA

2D目标检测(Object Detection)

DetCo: Unsupervised Contrastive Learning for Object Detection

Paper: https://arxiv.org/abs/2102.04803
Code: https://github.com/xieenze/DetCo

Detecting Invisible People

Homepage: http://www.cs.cmu.edu/~tkhurana/invisible.htm
Code: https://arxiv.org/abs/2012.08419

Active Learning for Deep Object Detection via Probabilistic Modeling

Paper: https://arxiv.org/abs/2103.16130
Code: None

Conditional Variational Capsule Network for Open Set Recognition

Paper: https://arxiv.org/abs/2104.09159
Code: https://github.com/guglielmocamporese/cvaecaposr

MDETR : Modulated Detection for End-to-End Multi-Modal Understanding

Homepage: https://ashkamath.github.io/mdetr_page/
Paper(Oral): https://arxiv.org/abs/2104.12763
Code: https://github.com/ashkamath/mdetr

Rank & Sort Loss for Object Detection and Instance Segmentation

Paper(Oral): https://arxiv.org/abs/2107.11669
Code: https://github.com/kemaloksuz/RankSortLoss

SimROD: A Simple Adaptation Method for Robust Object Detection

Paper(Oral): https://arxiv.org/abs/2107.13389
Code: None

GraphFPN: Graph Feature Pyramid Network for Object Detection

Paper: https://arxiv.org/abs/2108.00580
Code: None

Fast Convergence of DETR with Spatially Modulated Co-Attention

Paper: https://arxiv.org/abs/2101.07448
Code: https://github.com/abc403/SMCA-replication

Conditional DETR for Fast Training Convergence

Paper: https://arxiv.org/abs/2108.06152
Code: https://github.com/Atten4Vis/ConditionalDETR

TOOD: Task-aligned One-stage Object Detection

Paper(Oral): https://arxiv.org/abs/2108.07755
Code: https://github.com/fcjian/TOOD

Reconcile Prediction Consistency for Balanced Object Detection

Paper: https://arxiv.org/abs/2108.10809
Code: None

Mutual Supervision for Dense Object Detection

Paper: https://arxiv.org/abs/2109.05986
Code: https://github.com/MCG-NJU/MuSu-Detection

PnP-DETR: Towards Efficient Visual Analysis with Transformers

Paper: https://arxiv.org/abs/2109.07036
Code: https://github.com/twangnh/pnp-detr

Deep Structured Instance Graph for Distilling Object Detectors

Paper: https://arxiv.org/abs/2109.12862
Code: https://github.com/dvlab-research/Dsig

半监督目标检测

End-to-End Semi-Supervised Object Detection with Soft Teacher

Paper: https://arxiv.org/abs/2106.09018
Code: None

旋转目标检测

Oriented R-CNN for Object Detection

Paper: https://arxiv.org/abs/2108.05699
Code: https://github.com/jbwang1997/OBBDetection

Few-Shot目标检测

DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection

Paper: https://arxiv.org/abs/2108.09017
Code: https://github.com/er-muyue/DeFRCN

语义分割(Semantic Segmentation)

Personalized Image Semantic Segmentation

Paper: https://arxiv.org/abs/2107.13978
Code: https://github.com/zhangyuygss/PIS
Dataset: https://github.com/zhangyuygss/PIS

Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation

Paper(Oral): https://arxiv.org/abs/2107.11264
Code: None

Enhanced Boundary Learning for Glass-like Object Segmentation

Paper: https://arxiv.org/abs/2103.15734
Code: https://github.com/hehao13/EBLNet

Self-Regulation for Semantic Segmentation

Paper: https://arxiv.org/abs/2108.09702
Code: https://github.com/dongzhang89/SR-SS

Mining Contextual Information Beyond Image for Semantic Segmentation

Paper: https://arxiv.org/abs/2108.11819
Code: https://github.com/CharlesPikachu/mcibi

Standardized Max Logits: A Simple yet Effective Approach for Identifying Unexpected Road Obstacles in Urban-Scene Segmentation

Paper: https://arxiv.org/abs/2107.11264
Code: https://github.com/shjung13/Standardized-max-logits

ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation

Paper: https://arxiv.org/abs/2108.12382
Code: https://github.com/SegmentationBLWX/sssegmentation

Scaling up instance annotation via label propagation

Homepage: http://scaling-anno.csail.mit.edu/
Paper: https://arxiv.org/abs/2110.02277
Code: None

无监督域自适应语义分割(Unsupervised Domain Ddaption Semantic Segmentation)

Multi-Anchor Active Domain Adaptation for Semantic Segmentation

Paper(Oral): https://arxiv.org/abs/2108.08012
Code: https://github.com/munanning/MADA

Generalize then Adapt: Source-Free Domain Adaptive Semantic Segmentation

Homepage: https://sites.google.com/view/sfdaseg
Paper: https://arxiv.org/abs/2108.11249

Few-Shot语义分割

Learning Meta-class Memory for Few-Shot Semantic Segmentation

Paper: https://arxiv.org/abs/2108.02958'
Code: None

Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer

Paper: https://arxiv.org/abs/2108.03032
Code: https://github.com/zhiheLu/CWT-for-FSS

半监督语义分割(Semi-supervised Semantic Segmentation)

Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation

Paper: https://arxiv.org/abs/2107.11787
Code: None

Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigation

Paper(Oral): https://arxiv.org/abs/2107.11279
Code: https://github.com/CVMI-Lab/DARS

Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation

Paper: https://arxiv.org/abs/2108.09025
Code: None

弱监督语义分割(Weakly Supervised Semantic Segmentation)

Complementary Patch for Weakly Supervised Semantic Segmentation

Paper: https://arxiv.org/abs/2108.03852
Code: None

无监督分割(Unsupervised Segmentation)

Labels4Free: Unsupervised Segmentation using StyleGAN

Homepage: https://rameenabdal.github.io/Labels4Free/
Paper: https://arxiv.org/abs/2103.14968

实例分割(Instance Segmentation)

Instances as Queries

Paper: https://arxiv.org/abs/2105.01928
Code: https://github.com/hustvl/QueryInst

Crossover Learning for Fast Online Video Instance Segmentation

Paper: https://arxiv.org/abs/2104.05970
Code: https://github.com/hustvl/CrossVIS

Rank & Sort Loss for Object Detection and Instance Segmentation

Paper(Oral): https://arxiv.org/abs/2107.11669
Code: https://github.com/kemaloksuz/RankSortLoss

SOTR: Segmenting Objects with Transformers

Paper: https://arxiv.org/abs/2108.06747
Code: https://github.com/easton-cau/SOTR

Scaling up instance annotation via label propagation

Homepage: http://scaling-anno.csail.mit.edu/
Paper: https://arxiv.org/abs/2110.02277
Code: None

医学图像分割(Medical Image Segmentation)

Recurrent Mask Refinement for Few-Shot Medical Image Segmentation

Paper: https://arxiv.org/abs/2108.00622
Code: https://github.com/uci-cbcl/RP-Net

视频目标分割(Video Object Segmentation)

Hierarchical Memory Matching Network for Video Object Segmentation

Paper: https://arxiv.org/abs/2109.11404
Code: https://github.com/Hongje/HMMN

Full-Duplex Strategy for Video Object Segmentation

Homepage: http://dpfan.net/FSNet/
Paper: https://arxiv.org/abs/2108.03151
Code: https://github.com/GewelsJI/FSNet

Joint Inductive and Transductive Learning for Video Object Segmentation

Paper: https://arxiv.org/abs/2108.03679
Code: https://github.com/maoyunyao/JOINT

Few-shot Segmentation

Mining Latent Classes for Few-shot Segmentation

Paper(Oral): https://arxiv.org/abs/2103.15402
Code: https://github.com/LiheYoung/MiningFSS

人体运动分割(Human Motion Segmentation)

Graph Constrained Data Representation Learning for Human Motion Segmentation

Paper: https://arxiv.org/abs/2107.13362
Code: None

目标跟踪(Object Tracking)

Learning to Track Objects from Unlabeled Videos

Paper: https://arxiv.org/abs/2108.12711
Code: https://github.com/VISION-SJTU/USOT

Learning Spatio-Temporal Transformer for Visual Tracking

Paper: https://arxiv.org/abs/2103.17154
Code: https://github.com/researchmm/Stark

Learning to Adversarially Blur Visual Object Tracking

Paper: https://arxiv.org/abs/2107.12085
Code: https://github.com/tsingqguo/ABA

HiFT: Hierarchical Feature Transformer for Aerial Tracking

Paper: https://arxiv.org/abs/2108.00202
Code: https://github.com/vision4robotics/HiFT

Learn to Match: Automatic Matching Network Design for Visual Tracking

Paper: https://arxiv.org/abs/2108.00803
Code: https://github.com/JudasDie/SOTS

Saliency-Associated Object Tracking

Paper: https://arxiv.org/abs/2108.03637
Code: https://github.com/ZikunZhou/SAOT.git

RGBD 目标跟踪

DepthTrack: Unveiling the Power of RGBD Tracking

Paper: https://arxiv.org/abs/2108.13962
Code: https://github.com/xiaozai/DeT
Dataset: https://github.com/xiaozai/DeT

3D Point Cloud

Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds

Homepage: https://siyuanhuang.com/STRL/
Paper: https://arxiv.org/abs/2109.00179
Code: https://github.com/yichen928/STRL

Unsupervised Point Cloud Pre-Training via View-Point Occlusion, Completion

Homepage: https://hansen7.github.io/OcCo/
Paper: https://arxiv.org/abs/2010.01089
Code: https://github.com/hansen7/OcCo

DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation

Paper: https://arxiv.org/abs/2108.04023
Code: None

Adaptive Graph Convolution for Point Cloud Analysis

Paper: https://arxiv.org/abs/2108.08035
Code: https://github.com/hrzhou2/AdaptConv-master

Unsupervised Point Cloud Pre-Training via View-Point Occlusion, Completion

Paper: https://arxiv.org/abs/2010.01089
Code: https://github.com/hansen7/OcCo

3D Object Detection(3D目标检测)

Group-Free 3D Object Detection via Transformers

Paper: https://arxiv.org/abs/2104.00678
Code: None

Improving 3D Object Detection with Channel-wise Transformer

Paper: https://arxiv.org/abs/2108.10723
Code: https://github.com/hlsheng1/CT3D

AutoShape: Real-Time Shape-Aware Monocular 3D Object Detection

Paper: https://arxiv.org/abs/2108.11127
Code: https://github.com/zongdai/AutoShape

4D-Net for Learned Multi-Modal Alignment

Paper: https://arxiv.org/abs/2109.01066
Code: None

Voxel Transformer for 3D Object Detection

Paper: https://arxiv.org/abs/2109.02497
Code: None

Pyramid R-CNN: Towards Better Performance and Adaptability for 3D Object Detection

Paper: https://arxiv.org/abs/2109.02499
Code: None

An End-to-End Transformer Model for 3D Object Detection

Homepage: https://facebookresearch.github.io/3detr/
Paper: https://arxiv.org/abs/2109.08141
Code: https://github.com/facebookresearch/3detr

RangeDet: In Defense of Range View for LiDAR-based 3D Object Detection

Paper: https://arxiv.org/abs/2103.10039
Code: https://github.com/TuSimple/RangeDet

Geometry-based Distance Decomposition for Monocular 3D Object Detection

Paper: https://arxiv.org/abs/2104.03775
Code: https://github.com/Rock-100/MonoDet

3D Semantic Segmentation(3D语义分割)

ReDAL: Region-based and Diversity-aware Active Learning for Point Cloud Semantic Segmentation

Paper: https://arxiv.org/abs/2107.11769
Code: None

Learning with Noisy Labels for Robust Point Cloud Segmentation

Homepage: https://shuquanye.com/PNAL_website/
Paper(Oral): https://arxiv.org/abs/2107.14230

VMNet: Voxel-Mesh Network for Geodesic-Aware 3D Semantic Segmentation

Paper(Oral): https://arxiv.org/abs/2107.13824
Code: https://github.com/hzykent/VMNet

Sparse-to-dense Feature Matching: Intra and Inter domain Cross-modal Learning in Domain Adaptation for 3D Semantic Segmentation

Paper: https://arxiv.org/abs/2107.14724
Code: https://github.com/leolyj/DsCML

DRINet: A Dual-Representation Iterative Learning Network for Point Cloud Segmentation

Paper: https://arxiv.org/abs/2108.04023
Code: None

Adaptive Graph Convolution for Point Cloud Analysis

Paper: https://arxiv.org/abs/2108.08035
Code: https://github.com/hrzhou2/AdaptConv-master

Perception-Aware Multi-Sensor Fusion for 3D LiDAR Semantic Segmentation

Paper: https://arxiv.org/abs/2106.15277
Code: https://github.com/ICEORY/PMF

3D Instance Segmentation(3D实例分割)

Hierarchical Aggregation for 3D Instance Segmentation

Paper: https://arxiv.org/abs/2108.02350
Code: https://github.com/hustvl/HAIS

Instance Segmentation in 3D Scenes Using Semantic Superpoint Tree Networks

Paper: https://openaccess.thecvf.com/content/ICCV2021/html/Liang_Instance_Segmentation_in_3D_Scenes_Using_Semantic_Superpoint_Tree_Networks_ICCV_2021_paper.html
Code: https://github.com/Gorilla-Lab-SCUT/SSTNet

3D Multi-Object Tracking(3D多目标跟踪)

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving

Paper: https://arxiv.org/abs/2108.10312
Code: https://github.com/qcraftai/simtrack

Point Cloud Denoising(点云去噪)

Score-Based Point Cloud Denoising

Paper: https://arxiv.org/abs/2107.10981
Code: None

Point Cloud Registration(点云配准)

HRegNet: A Hierarchical Network for Large-scale Outdoor LiDAR Point Cloud Registration

Homepage: https://ispc-group.github.io/hregnet
Paper: https://arxiv.org/abs/2107.11992
Code: https://github.com/ispc-lab/HRegNet

A Robust Loss for Point Cloud Registration

Paper: https://arxiv.org/abs/2108.11682
Code: None

Point Cloud Completion(点云补全)

PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

Paper(Oral): https://arxiv.org/abs/2108.08839
Code: https://github.com/yuxumin/PoinTr

SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

Paper: https://arxiv.org/abs/2108.04444
Code: https://github.com/AllenXiangX/SnowflakeNet

雷达语义分割(Radar Semantic Segmentation)

Multi-View Radar Semantic Segmentation

Paper: https://arxiv.org/abs/2103.16214
Code: https://github.com/valeoai/MVRSS

图像恢复(Image Restoration)

Dynamic Attentive Graph Learning for Image Restoration

Paper: https://arxiv.org/abs/2109.06620
Code: https://github.com/jianzhangcs/DAGL

超分辨率(Super-Resolution)

Learning for Scale-Arbitrary Super-Resolution from Scale-Specific Networks

Paper: https://arxiv.org/abs/2004.03791
Code: https://github.com/LongguangWang/ArbSR

Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution

Paper: https://arxiv.org/abs/2108.05302
Code: https://github.com/JingyunLiang/MANet

Deep Reparametrization of Multi-Frame Super-Resolution and Denoising

Paper(Oral): https://arxiv.org/abs/2108.08286
Code: None

Dual-Camera Super-Resolution with Aligned Attention Modules

Homepage: https://tengfei-wang.github.io/Dual-Camera-SR/index.html
Paper: https://arxiv.org/abs/2109.01349
Code: https://github.com/Tengfei-Wang/DualCameraSR
Dataset: https://tengfei-wang.github.io/Dual-Camera-SR/index.html

Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme

Paper: https://www4.comp.polyu.edu.hk/~cslzhang/paper/ICCV21_RealVSR.pdf
Code: https://github.com/IanYeung/RealVSR
Dataset: https://github.com/IanYeung/RealVSR

去噪(Denoising)

Deep Reparametrization of Multi-Frame Super-Resolution and Denoising

Paper(Oral): https://arxiv.org/abs/2108.08286
Code: None

Rethinking Deep Image Prior for Denoising

Paper: https://arxiv.org/abs/2108.12841
Code: https://github.com/gistvision/DIP-denosing

医学图像去噪(Medical Image Denoising)

Eformer: Edge Enhancement based Transformer for Medical Image Denoising

Paper: https://arxiv.org/abs/2109.08044
Code: None

去模糊(Deblurring)

Rethinking Coarse-to-Fine Approach in Single Image Deblurring

Paper: https://arxiv.org/abs/2108.05054
Code: https://github.com/chosj95/MIMO-UNet

Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions

Paper: https://arxiv.org/abs/2108.09108
Code: None

阴影去除(Shadow Removal)

CANet: A Context-Aware Network for Shadow Removal

Paper: https://arxiv.org/abs/2108.09894
Code: https://github.com/Zipei-Chen/CANet

视频插帧(Video Frame Interpolation)

XVFI: eXtreme Video Frame Interpolation

Paper(Oral): https://arxiv.org/abs/2103.16206
Code: https://github.com/JihyongOh/XVFI
Dataset: https://github.com/JihyongOh/XVFI

Asymmetric Bilateral Motion Estimation for Video Frame Interpolation

Paper: https://arxiv.org/abs/2108.06815
Code: https://github.com/JunHeum/ABME

视频修复/补全(Video Inpainting)

FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting

Paper: https://arxiv.org/abs/2109.02974
Code: https://github.com/ruiliu-ai/FuseFormer

行人重识别(Person Re-identification)

TransReID: Transformer-based Object Re-Identification

Paper: https://arxiv.org/abs/2102.04378
Code: https://github.com/heshuting555/TransReID

IDM: An Intermediate Domain Module for Domain Adaptive Person Re-ID

Paper(Oral): https://arxiv.org/abs/2108.02413
Code: https://github.com/SikaStar/IDM

行人搜索(Person Search)

Weakly Supervised Person Search with Region Siamese Networks

Paper: https://arxiv.org/abs/2109.06109
Code: None

2D/3D人体姿态估计(2D/3D Human Pose Estimation)

2D 人体姿态估计

Human Pose Regression with Residual Log-likelihood Estimation

Paper(Oral): https://arxiv.org/abs/2107.11291
Code(RLE): https://github.com/Jeff-sjtu/res-loglikelihood-regression

Online Knowledge Distillation for Efficient Pose Estimation

Paper: https://arxiv.org/abs/2108.02092
Code: None

3D 人体姿态估计

Probabilistic Monocular 3D Human Pose Estimation with Normalizing Flows

Paper: https://arxiv.org/abs/2107.13788
Code: https://github.com/twehrbein/Probabilistic-Monocular-3D-Human-Pose-Estimation-with-Normalizing-Flows

Graph-Based 3D Multi-Person Pose Estimation Using Multi-View Images

Paper: https://arxiv.org/abs/2109.05885
Code: None

6D位姿估计(6D Object Pose Estimation)

StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation

Paper: https://arxiv.org/abs/2109.10115
Code: None
Dataset: None

3D人头重建(3D Head Reconstruction)

H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction

Homepage: https://crisalixsa.github.io/h3d-net/
Paper: https://arxiv.org/abs/2107.12512

人脸识别(Face Recognition)

SynFace: Face Recognition with Synthetic Data

Paper: https://arxiv.org/abs/2108.07960
Code: None

Facial Expression Recognition(人脸表情识别)

TransFER: Learning Relation-aware Facial Expression Representations with Transformers

Paper: https://arxiv.org/abs/2108.11116
Code: None

行为识别(Action Recognition)

MGSampler: An Explainable Sampling Strategy for Video Action Recognition

Paper: https://arxiv.org/abs/2104.09952
Code: None

Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition

Paper: https://arxiv.org/abs/2107.12213
Code: https://github.com/Uason-Chen/CTR-GCN

Enhancing Self-supervised Video Representation Learning via Multi-level Feature Optimization

Paper: https://arxiv.org/abs/2108.02183
Code: None

Dynamic Network Quantization for Efficient Video Inference

Homepage: https://cs-people.bu.edu/sunxm/VideoIQ/project.html
Paper: https://arxiv.org/abs/2108.10394
Code: https://github.com/sunxm2357/VideoIQ

时序动作定位(Temporal Action Localization)

Enriching Local and Global Contexts for Temporal Action Localization

Paper: https://arxiv.org/abs/2107.12960
Code: None

动作检测(Action Detection)

Class Semantics-based Attention for Action Detection

Paper: https://arxiv.org/abs/2109.02613
Code: None

群体活动识别(Group Activity Recognition)

GroupFormer: Group Activity Recognition with Clustered Spatial-Temporal Transformer

Paper: https://arxiv.org/abs/2108.12630
Code: https://github.com/xueyee/GroupFormer

手语识别(Sign Language Recognition)

Visual Alignment Constraint for Continuous Sign Language Recognition

Paper: https://arxiv.org/abs/2104.02330
Code: https://github.com/ycmin95/VAC_CSLR

文本检测(Text Detection)

Adaptive Boundary Proposal Network for Arbitrary Shape Text Detection

Paper: https://arxiv.org/abs/2107.12664
Code: https://github.com/GXYM/TextBPN

文本识别(Text Recognition)

Joint Visual Semantic Reasoning: Multi-Stage Decoder for Text Recognition

Paper: https://arxiv.org/abs/2107.12090
Code: None

文本替换(Text Replacement)

STRIVE: Scene Text Replacement In Videos

Homepage: https://striveiccv2021.github.io/STRIVE-ICCV2021/
Paper: https://arxiv.org/abs/2109.02762
Code: https://github.com/striveiccv2021/STRIVE-ICCV2021/
Datasets: https://github.com/striveiccv2021/STRIVE-ICCV2021/

视觉问答(Visual Question Answering, VQA)

Greedy Gradient Ensemble for Robust Visual Question Answering

Paper: https://arxiv.org/abs/2107.12651
Code: https://github.com/GeraldHan/GGE

对抗攻击(Adversarial Attack)

Feature Importance-aware Transferable Adversarial Attacks

Paper: https://arxiv.org/abs/2107.14185
Code: https://github.com/hcguoO0/FIA

AdvDrop: Adversarial Attack to DNNs by Dropping Information

Paper: https://arxiv.org/abs/2108.09034
Code: https://github.com/RjDuan/AdvDrop

深度估计(Depth Estimation)

Augmenting Depth Estimation with Geospatial Context

Paper: https://arxiv.org/abs/2109.09879
Code: None

NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereo

Paper(Oral): https://arxiv.org/abs/2109.01129
Code: https://github.com/weiyithu/NerfingMVS

单目深度估计

MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments

Paper: https://arxiv.org/abs/2107.12429
Code: None

Towards Interpretable Deep Networks for Monocular Depth Estimation

Paper: https://arxiv.org/abs/2108.05312
Code: https://github.com/youzunzhi/InterpretableMDE

Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark

Paper: https://arxiv.org/abs/2108.03830
Code: https://github.com/w2kun/RNW

Self-supervised Monocular Depth Estimation for All Day Images using Domain Separation

Paper: https://arxiv.org/abs/2108.07628
Code: https://github.com/LINA-lln/ADDS-DepthNet

StructDepth: Leveraging the structural regularities for self-supervised indoor depth estimation

Paper: https://arxiv.org/abs/2108.08574
Code: https://github.com/SJTU-ViSYS/StructDepth

视线估计(Gaze Estimation)

Generalizing Gaze Estimation with Outlier-guided Collaborative Adaptation

Paper: https://arxiv.org/abs/2107.13780
Code: https://github.com/DreamtaleCore/PnP-GA

人群计数(Crowd Counting)

Rethinking Counting and Localization in Crowds:A Purely Point-Based Framework

Paper(Oral): https://arxiv.org/abs/2107.12746
Code(P2PNet): https://github.com/TencentYoutuResearch/CrowdCounting-P2PNet

Uniformity in Heterogeneity:Diving Deep into Count Interval Partition for Crowd Counting

Paper: https://arxiv.org/abs/2107.12619
Code: https://github.com/TencentYoutuResearch/CrowdCounting-UEPNet

车道线检测(Lane-Detection)

VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection

Paper: https://arxiv.org/abs/2108.08482
Code: https://github.com/yujun0-0/MMA-Net
Dataset: https://github.com/yujun0-0/MMA-Net

轨迹预测(Trajectory Prediction)

Human Trajectory Prediction via Counterfactual Analysis

Paper: https://arxiv.org/abs/2107.14202
Code: https://github.com/CHENGY12/CausalHTP

Personalized Trajectory Prediction via Distribution Discrimination

Paper: https://arxiv.org/abs/2107.14204
Code: https://github.com/CHENGY12/DisDis

MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction

Paper: https://arxiv.org/abs/2108.09274
Code: https://github.com/selflein/MG-GAN

Social NCE: Contrastive Learning of Socially-aware Motion Representations

Paper: https://arxiv.org/abs/2012.11717
Code: https://github.com/vita-epfl/social-nce

Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving

Paper: https://arxiv.org/abs/2109.01510
Code: https://github.com/xrenaa/Safety-Aware-Motion-Prediction

Where are you heading? Dynamic Trajectory Prediction with Expert Goal Examples

Paper: https://openaccess.thecvf.com/content/ICCV2021/papers/Zhao_Where_Are_You_Heading_Dynamic_Trajectory_Prediction_With_Expert_Goal_ICCV_2021_paper.pdf
Code: https://github.com/JoeHEZHAO/expert_traj

异常检测(Anomaly Detection)

Weakly-supervised Video Anomaly Detection with Robust Temporal Feature Magnitude Learning

Paper: https://arxiv.org/abs/2101.10030
Code: https://github.com/tianyu0207/RTFM

场景图生成(Scene Graph Generation)

Spatial-Temporal Transformer for Dynamic Scene Graph Generation

Paper: https://arxiv.org/abs/2107.12309
Code: None

图像编辑(Image Editing)

Sketch Your Own GAN

Homepage: https://peterwang512.github.io/GANSketching/
Paper: https://arxiv.org/abs/2108.02774
代码: https://github.com/peterwang512/GANSketching

图像合成(Image Synthesis)

Image Synthesis via Semantic Composition

Homepage: https://shepnerd.github.io/scg/
Paper: https://arxiv.org/abs/2109.07053
Code: https://github.com/dvlab-research/SCGAN

图像检索(Image Retrieval)

Self-supervised Product Quantization for Deep Unsupervised Image Retrieval

Paper: https://arxiv.org/abs/2109.02244
Code: https://github.com/youngkyunJang/SPQ

三维重建(3D Reconstruction)

Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction

Paper: https://arxiv.org/abs/2109.00512
Code: https://github.com/facebookresearch/co3d
Dataset: https://github.com/facebookresearch/co3d

视频稳像(Video Stabilization)

Out-of-boundary View Synthesis Towards Full-Frame Video Stabilization

Paper: https://arxiv.org/abs/2108.09041
代码：https://github.com/Annbless/OVS_Stabilization

细粒度识别(Fine-Grained Recognition)

Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach

Paper: https://arxiv.org/abs/2108.02399
Code: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset
Dataset: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset

风格迁移(Style Transfer)

AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer

Paper: https://arxiv.org/abs/2108.03647
Paddle Code：https://github.com/PaddlePaddle/PaddleGAN
PyTorch Code：https://github.com/Huage001/AdaAttN

神经绘画(Neural Painting)

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction

Paper: https://arxiv.org/abs/2108.03798
Code: https://github.com/wzmsltw/PaintTransformer

特征匹配(Feature Matching)

Learning to Match Features with Seeded Graph Matching Network

Paper: https://arxiv.org/abs/2108.08771
Code: https://github.com/vdvchen/SGMNet

语义对应(Semantic Correspondence)

Multi-scale Matching Networks for Semantic Correspondence

Paper: https://arxiv.org/abs/2108.00211
Code: https://github.com/wintersun661/MMNet

边缘检测(Edge Detection)

Pixel Difference Networks for Efficient Edge Detection

Paper: https://arxiv.org/abs/2108.07009
Code: https://github.com/zhuoinoulu/pidinet

RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth

Paper: https://arxiv.org/abs/2108.00616
Code : https://github.com/MengyangPu/RINDNet
Dataset: https://github.com/MengyangPu/RINDNet

相机标定(Camera calibration)

CTRL-C: Camera calibration TRansformer with Line-Classification

Paper: https://arxiv.org/abs/2109.02259
Code: https://github.com/jwlee-vcl/CTRL-C

图像质量评估(Image Quality Assessment)

MUSIQ: Multi-scale Image Quality Transformer

Paper: https://arxiv.org/abs/2108.05997
Code: https://github.com/google-research/google-research/tree/master/musiq

Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment

Paper: https://arxiv.org/abs/2108.07948
Code: https://github.com/researchmm/CKDN

度量学习(Metric Learning)

Deep Relational Metric Learning

Paper: https://arxiv.org/abs/2108.10026
Code: https://github.com/zbr17/DRML

Towards Interpretable Deep Metric Learning with Structural Matching

Paper: https://arxiv.org/abs/2108.05889
Code: https://github.com/wl-zhao/DIML

Unsupervised Domain Adaptation

Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptation

Paper(Oral): https://arxiv.org/abs/2107.13467
Code: None

Video Rescaling

Self-Conditioned Probabilistic Learning of Video Rescaling

Paper: https://arxiv.org/abs/2107.11639
Code: None

Hand-Object Interaction

Learning a Contact Potential Field to Model the Hand-Object Interaction

Paper: https://arxiv.org/abs/2012.00924
Code: https://lixiny.github.io/CPF

Vision-and-Language Navigation

Airbert: In-domain Pretraining for Vision-and-Language Navigation

Paper: https://arxiv.org/abs/2108.09105
Code: https://airbert-vln.github.io/
Dataset: https://airbert-vln.github.io/

数据集(Datasets)

Beyond Road Extraction: A Dataset for Map Update using Aerial Images

Homepage: https://favyen.com/muno21/
Paper: https://arxiv.org/abs/2110.04690
Code: https://github.com/favyen/muno21

StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation

Paper: https://arxiv.org/abs/2109.10115
Code: None
Dataset: None

RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth

Paper: https://arxiv.org/abs/2108.00616
Code : https://github.com/MengyangPu/RINDNet
Dataset: https://github.com/MengyangPu/RINDNet

Panoptic Narrative Grounding

Homepage: https://bcv-uniandes.github.io/panoptic-narrative-grounding/
Paper(Oral): https://arxiv.org/abs/2109.04988
Code: https://github.com/BCV-Uniandes/PNG
Dataset: https://github.com/BCV-Uniandes/PNG

STRIVE: Scene Text Replacement In Videos

Homepage: https://striveiccv2021.github.io/STRIVE-ICCV2021/
Paper: https://arxiv.org/abs/2109.02762
Code: https://github.com/striveiccv2021/STRIVE-ICCV2021/
Datasets: https://github.com/striveiccv2021/STRIVE-ICCV2021/

Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme

Paper: https://www4.comp.polyu.edu.hk/~cslzhang/paper/ICCV21_RealVSR.pdf
Code: https://github.com/IanYeung/RealVSR
Dataset: https://github.com/IanYeung/RealVSR

Matching in the Dark: A Dataset for Matching Image Pairs of Low-light Scenes

Paper: https://arxiv.org/abs/2109.03585
Code: None

Dual-Camera Super-Resolution with Aligned Attention Modules

Homepage: https://tengfei-wang.github.io/Dual-Camera-SR/index.html
Paper: https://arxiv.org/abs/2109.01349
Code: https://github.com/Tengfei-Wang/DualCameraSR
Dataset: https://tengfei-wang.github.io/Dual-Camera-SR/index.html

DepthTrack: Unveiling the Power of RGBD Tracking

Paper: https://arxiv.org/abs/2108.13962
Code: https://github.com/xiaozai/DeT
Dataset: https://github.com/xiaozai/DeT

Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction

Paper: https://arxiv.org/abs/2109.00512
Code: https://github.com/facebookresearch/co3d
Dataset: https://github.com/facebookresearch/co3d

BioFors: A Large Biomedical Image Forensics Dataset

Paper: https://arxiv.org/abs/2108.12961
Code: None
Dataset: None

Webly Supervised Fine-Grained Recognition: Benchmark Datasets and An Approach

Paper: https://arxiv.org/abs/2108.02399
Code: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset
Dataset: https://github.com/NUST-Machine-Intelligence-Laboratory/weblyFG-dataset

Airbert: In-domain Pretraining for Vision-and-Language Navigation

Paper: https://arxiv.org/abs/2108.09105
Code: https://airbert-vln.github.io/
Dataset: https://airbert-vln.github.io/

Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation

Paper: http://arxiv.org/abs/2108.08202
Code: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021
Dataset: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021

VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection

Paper: https://arxiv.org/abs/2108.08482
Code: https://github.com/yujun0-0/MMA-Net
Dataset: https://github.com/yujun0-0/MMA-Net

XVFI: eXtreme Video Frame Interpolation

Paper(Oral): https://arxiv.org/abs/2103.16206
Code: https://github.com/JihyongOh/XVFI
Dataset: https://github.com/JihyongOh/XVFI

Personalized Image Semantic Segmentation

Paper: https://arxiv.org/abs/2107.13978
Code: https://github.com/zhangyuygss/PIS
Dataset: https://github.com/zhangyuygss/PIS

H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction

Homepage: https://crisalixsa.github.io/h3d-net/
Paper: https://arxiv.org/abs/2107.12512

其他(Others)

Photon-Starved Scene Inference using Single Photon Cameras

Paper: https://openaccess.thecvf.com/content/ICCV2021/papers/Goyal_Photon-Starved_Scene_Inference_Using_Single_Photon_Cameras_ICCV_2021_paper.pdf
Code: https://github.com/bhavyagoyal/spclowlight

Towards Flexible Blind JPEG Artifacts Removal

Paper: https://arxiv.org/abs/2109.14573
Code: https://github.com/jiaxi-jiang/FBCNN

Generating Attribution Maps with Disentangled Masked Backpropagation

Paper: https://arxiv.org/abs/2101.06773
Code: https://gitlab.com/adriaruizo/dmbp_iccv21

CrossCLR: Cross-modal Contrastive Learning For Multi-modal Video Representations

Paper: https://arxiv.org/abs/2109.14910
Code: None

ReconfigISP: Reconfigurable Camera Image Processing Pipeline

Paper: https://arxiv.org/abs/2109.04760
Code: None

Panoptic Narrative Grounding

Homepage: https://bcv-uniandes.github.io/panoptic-narrative-grounding/
Paper(Oral): https://arxiv.org/abs/2109.04988
Code: https://github.com/BCV-Uniandes/PNG
Dataset: https://github.com/BCV-Uniandes/PNG

NEAT: Neural Attention Fields for End-to-End Autonomous Driving

Paper: https://arxiv.org/abs/2109.04456
https://github.com/autonomousvision/neat

Keep CALM and Improve Visual Feature Attribution

Paper: https://arxiv.org/abs/2106.07861
Code: https://github.com/naver-ai/calm

YouRefIt: Embodied Reference Understanding with Language and Gesture

Paper: https://arxiv.org/abs/2109.03413
Code: None

Pri3D: Can 3D Priors Help 2D Representation Learning?

Paper: https://arxiv.org/abs/2104.11225
Code: https://github.com/Sekunde/Pri3D

Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

Paper: https://arxiv.org/abs/2108.08487
Code: https://github.com/iCGY96/APR

Continual Learning for Image-Based Camera Localization

Paper: https://arxiv.org/abs/2108.09112
Code: None

Multi-Task Self-Training for Learning General Representations

Paper: https://arxiv.org/abs/2108.11353
Code: None

A Unified Objective for Novel Class Discovery

Homepage: https://ncd-uno.github.io/
Paper(Oral): https://arxiv.org/abs/2108.08536
Code: https://github.com/DonkeyShot21/UNO

Global Pooling, More than Meets the Eye: Position Information is Encoded Channel-Wise in CNNs

Paper: https://arxiv.org/abs/2108.07884
Code: https://github.com/islamamirul/PermuteNet

Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation

Paper: http://arxiv.org/abs/2108.08202
Code: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021
Dataset: https://github.com/Neural-video-delivery/CaFM-Pytorch-ICCV2021

Impact of Aliasing on Generalizatin in Deep Convolutional Networks

Paper: https://arxiv.org/abs/2108.03489
Code: None

Out-of-Core Surface Reconstruction via Global TGV Minimization

Paper: https://arxiv.org/abs/2107.14790
Code: None

Progressive Correspondence Pruning by Consensus Learning

Homepage: https://sailor-z.github.io/projects/CLNet.html
Paper: https://arxiv.org/abs/2101.00591
Code: https://github.com/sailor-z/CLNet

Energy-Based Open-World Uncertainty Modeling for Confidence Calibration

Paper: https://arxiv.org/abs/2107.12628
Code: None

Generalized Shuffled Linear Regression

Paper: https://drive.google.com/file/d/1Qu21VK5qhCW8WVjiRnnBjehrYVmQrDNh/view?usp=sharing
Code: https://github.com/SILI1994/Generalized-Shuffled-Linear-Regression

Discovering 3D Parts from Image Collections

Homepage: https://chhankyao.github.io/lpd/
Paper: https://arxiv.org/abs/2107.13629

Semi-Supervised Active Learning with Temporal Output Discrepancy

Paper: https://arxiv.org/abs/2107.14153
Code: https://github.com/siyuhuang/TOD

Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?

Paper: https://arxiv.org/abs/2105.02498

Code: https://github.com/KingJamesSong/DifferentiableSVD

Hand-Object Contact Consistency Reasoning for Human Grasps Generation

Homepage: https://hwjiang1510.github.io/GraspTTA/
Paper(Oral): https://arxiv.org/abs/2104.03304
Code: None

Equivariant Imaging: Learning Beyond the Range Space

Paper(Oral): https://arxiv.org/abs/2103.14756
Code: https://github.com/edongdongchen/EI

Just Ask: Learning to Answer Questions from Millions of Narrated Videos

Paper(Oral): https://arxiv.org/abs/2012.00451
Code: https://github.com/antoyang/just-ask

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Metadata

ICCV2021-Papers-with-Code

【ICCV 2021 论文和开源目录】

Backbone

Visual Transformer

涨点神器

GAN

NAS

NeRF

Loss

Zero-Shot Learning

Few-Shot Learning

长尾(Long-tailed)

Vision and Language

无监督/自监督(Un/Self-Supervised)

Multi-Label Image Recognition(多标签图像识别)

2D目标检测(Object Detection)

半监督目标检测

旋转目标检测

Few-Shot目标检测

语义分割(Semantic Segmentation)

无监督域自适应语义分割(Unsupervised Domain Ddaption Semantic Segmentation)

Few-Shot语义分割

半监督语义分割(Semi-supervised Semantic Segmentation)

弱监督语义分割(Weakly Supervised Semantic Segmentation)

无监督分割(Unsupervised Segmentation)

实例分割(Instance Segmentation)

医学图像分割(Medical Image Segmentation)

视频目标分割(Video Object Segmentation)

Few-shot Segmentation

人体运动分割(Human Motion Segmentation)

目标跟踪(Object Tracking)

RGBD 目标跟踪

3D Point Cloud

3D Object Detection(3D目标检测)

3D Semantic Segmentation(3D语义分割)

3D Instance Segmentation(3D实例分割)

3D Multi-Object Tracking(3D多目标跟踪)

Point Cloud Denoising(点云去噪)

Point Cloud Registration(点云配准)

Point Cloud Completion(点云补全)

雷达语义分割(Radar Semantic Segmentation)

图像恢复(Image Restoration)

超分辨率(Super-Resolution)

去噪(Denoising)

医学图像去噪(Medical Image Denoising)

去模糊(Deblurring)

阴影去除(Shadow Removal)

视频插帧(Video Frame Interpolation)

视频修复/补全(Video Inpainting)

行人重识别(Person Re-identification)

行人搜索(Person Search)

2D/3D人体姿态估计(2D/3D Human Pose Estimation)

2D 人体姿态估计

3D 人体姿态估计

6D位姿估计(6D Object Pose Estimation)

3D人头重建(3D Head Reconstruction)

人脸识别(Face Recognition)

Facial Expression Recognition(人脸表情识别)

行为识别(Action Recognition)

时序动作定位(Temporal Action Localization)

动作检测(Action Detection)

群体活动识别(Group Activity Recognition)

手语识别(Sign Language Recognition)

文本检测(Text Detection)

文本识别(Text Recognition)

文本替换(Text Replacement)

视觉问答(Visual Question Answering, VQA)

对抗攻击(Adversarial Attack)

深度估计(Depth Estimation)

单目深度估计

视线估计(Gaze Estimation)

人群计数(Crowd Counting)

车道线检测(Lane-Detection)

轨迹预测(Trajectory Prediction)

异常检测(Anomaly Detection)

场景图生成(Scene Graph Generation)

图像编辑(Image Editing)

图像合成(Image Synthesis)

ICCV2023-Papers-with-Code
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