Awesome-ECCV2022-Low-Level-Vision

A Collection of Papers and Codes in ECCV2022 related to Low-Level Vision

Related collections for low-level vision

• CVPR2022-Low-Level-Vision
• Awesome-AAAI2022-Low-Level-Vision
• Awesome-NeurIPS2021-Low-Level-Vision
• Awesome-ICCV2021-Low-Level-Vision
• Awesome-CVPR2021/CVPR2020-Low-Level-Vision
• Awesome-ECCV2020-Low-Level-Vision

Catalogue

• Image Restoration

• Super Resolution
  • Image Super Resolution
  • Video Super Resolution

• Denoising

  • Image Denoising
  • Video Denoising

• Deblurring

  • Image Deblurring
  • Video Deblurring

• Image Decomposition

• Dehazing

• Demoireing

• HDR Imaging / Multi-Exposure Image Fusion

• Frame Interpolation

  • Spatial-Temporal Video Super-Resolution

• Image Enhancement

  • Low-Light Image Enhancement

• Image Harmonization

• Image Completion/Inpainting

• Image Colorization

• Image Matting

• Shadow Removal

• Image Compression

• Image Quality Assessment

• Style Transfer

• Image Editing

• Image Generation/Synthesis/ Image-to-Image Translation

  • Video Generation

• Others

Image Restoration - 图像恢复

Simple Baselines for Image Restoration

• Paper: https://arxiv.org/abs/2204.04676
• Code: https://github.com/megvii-research/NAFNet

D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration

• Paper: https://arxiv.org/abs/2207.03294
• Code: https://github.com/zhaoyuzhi/D2HNet

Seeing Far in the Dark with Patterned Flash

• Paper:
• Code: https://github.com/zhsun0357/Seeing-Far-in-the-Dark-with-Patterned-Flash

BayesCap: Bayesian Identity Cap for Calibrated Uncertainty in Frozen Neural Networks

• Paper: https://arxiv.org/abs/2207.06873
• Code: https://github.com/ExplainableML/BayesCap

Improving Image Restoration by Revisiting Global Information Aggregation

• Paper: https://arxiv.org/abs/2112.04491
• Code: https://github.com/megvii-research/TLC

Fast Two-step Blind Optical Aberration Correction

• Paper: https://arxiv.org/abs/2208.00950
• Code: https://github.com/teboli/fast_two_stage_psf_correction
• Tags: Optical Aberration Correction

VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder

• Paper: https://arxiv.org/abs/2205.06803
• Code: https://github.com/TencentARC/VQFR
• Tags: Blind Face Restoration

RAWtoBit: A Fully End-to-end Camera ISP Network

• Paper: https://arxiv.org/abs/2208.07639
• Tags: ISP and Image Compression

Single Frame Atmospheric Turbulence Mitigation: A Benchmark Study and A New Physics-Inspired Transformer Model

• Paper: https://arxiv.org/abs/2207.10040
• Code: https://github.com/VITA-Group/TurbNet
• Tags: Atmospheric Turbulence Mitigation, Transformer

Modeling Mask Uncertainty in Hyperspectral Image Reconstruction

• Paper: https://arxiv.org/abs/2112.15362
• Code: https://github.com/Jiamian-Wang/mask_uncertainty_spectral_SCI
• Tags: Hyperspectral Image Reconstruction

Super Resolution - 超分辨率

Image Super Resolution

ARM: Any-Time Super-Resolution Method

• Paper: https://arxiv.org/abs/2203.10812
• Code: https://github.com/chenbong/ARM-Net

Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks

• Paper: https://arxiv.org/abs/2203.03844
• Code: https://github.com/zysxmu/DDTB

Learning Mutual Modulation for Self-Supervised Cross-Modal Super-Resolution

• Paper: https://arxiv.org/abs/2207.09156
• Code: https://github.com/palmdong/MMSR
• Tags: Self-Supervised

Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations

• Paper: https://arxiv.org/abs/2203.01325
• Code: https://github.com/cszhilu1998/SelfDZSR
• Tags: Self-Supervised

CADyQ : Contents-Aware Dynamic Quantization for Image Super Resolution

• Paper: https://arxiv.org/abs/2207.10345
• Code: https://github.com/Cheeun/CADyQ

From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution

• Paper:
• Code: https://github.com/csxmli2016/ReDegNet

Super-Resolution by Predicting Offsets: An Ultra-Efficient Super-Resolution Network for Rasterized Images

• Paper:
• Code: https://github.com/HaomingCai/SRPO

Learning Series-Parallel Lookup Tables for Efficient Image Super-Resolution

• Paper: https://arxiv.org/abs/2207.12987
• Code: https://github.com/zhjy2016/SPLUT

KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution

• Paper:
• Code: https://github.com/jiahong-fu/KXNet

Image Super-Resolution with Deep Dictionary

• Paper: https://arxiv.org/abs/2207.09228
• Code: https://github.com/shuntama/srdd

Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution

• Paper: http://www4.comp.polyu.edu.hk/~cslzhang/paper/ECCV2022_DASR.pdf
• Code: https://github.com/csjliang/DASR

Adaptive Patch Exiting for Scalable Single Image Super-Resolution

• Paper:
• Code: https://github.com/littlepure2333/APE

Efficient Long-Range Attention Network for Image Super-resolution

• Paper: https://arxiv.org/abs/2203.06697
• Code: https://github.com/xindongzhang/ELAN

Perception-Distortion Balanced ADMM Optimization for Single-Image Super-Resolution

• Paper: https://arxiv.org/abs/2208.03324
• Code: https://github.com/Yuehan717/PDASR

D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution

• Paper: https://arxiv.org/abs/2103.14373
• Code: https://github.com/megvii-research/D2C-SR
• Tag: Real-World

Reference-based Image Super-Resolution with Deformable Attention Transformer

• Paper: https://arxiv.org/abs/2207.11938
• Code: https://github.com/caojiezhang/DATSR
• Tags: Reference-based, Transformer

Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution

• Paper: https://arxiv.org/abs/2207.12577
• Code: https://github.com/wuyushuwys/compiler-aware-nas-sr

HST: Hierarchical Swin Transformer for Compressed Image Super-resolution

• Paper: https://arxiv.org/abs/2208.09885
• Tags: [Workshop-AIM2022]

Video Super Resolution

Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution

• Paper: https://arxiv.org/abs/2208.03012
• Code: https://github.com/researchmm/FTVSR
• Tags: Compressed Video SR

Denoising - 去噪

Image Denoising

Deep Semantic Statistics Matching (D2SM) Denoising Network

• Paper: https://arxiv.org/abs/2207.09302
• Code: https://github.com/MKFMIKU/d2sm

Video Denoising

Unidirectional Video Denoising by Mimicking Backward Recurrent Modules with Look-ahead Forward Ones

• Paper:
• Code: https://github.com/nagejacob/FloRNN

Deblurring - 去模糊

Image Deblurring

Learning Degradation Representations for Image Deblurring

• Paper: https://arxiv.org/abs/2208.05244
• Code: https://github.com/dasongli1/Learning_degradation

Animation from Blur: Multi-modal Blur Decomposition with Motion Guidance

• Paper: https://arxiv.org/abs/2207.10123
• Code: https://github.com/zzh-tech/Animation-from-Blur
• Tags: recovering detailed motion from a single motion-blurred image

Event-based Fusion for Motion Deblurring with Cross-modal Attention

• Paper:https://arxiv.org/abs/2112.00167
• Code: https://github.com/AHupuJR/EFNet
• Tags: Event-based

Video Deblurring

Spatio-Temporal Deformable Attention Network for Video Deblurring

• Paper: https://arxiv.org/abs/2207.10852
• Code: https://github.com/huicongzhang/STDAN

Efficient Video Deblurring Guided by Motion Magnitude

• Paper: https://arxiv.org/abs/2207.13374
• Code: https://github.com/sollynoay/MMP-RNN

DeMFI: Deep Joint Deblurring and Multi-Frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting

• Paper: https://arxiv.org/abs/2111.09985
• Code: https://github.com/JihyongOh/DeMFI
• Tags: Joint Deblurring and Frame Interpolation

Image Decomposition

Blind Image Decomposition

• Paper: https://arxiv.org/abs/2108.11364
• Code: https://github.com/JunlinHan/BID

Dehazing - 去雾

Frequency and Spatial Dual Guidance for Image Dehazing

• Paper:
• Code: https://github.com/yuhuUSTC/FSDGN

Perceiving and Modeling Density is All You Need for Image Dehazing

• Paper: https://arxiv.org/abs/2111.09733
• Code: https://github.com/Owen718/ECCV22-Perceiving-and-Modeling-Density-for-Image-Dehazing

Demoireing - 去摩尔纹

Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing

• Paper: https://arxiv.org/abs/2207.09935
• Code: https://github.com/XinYu-Andy/uhdm-page

HDR Imaging / Multi-Exposure Image Fusion - HDR图像生成 / 多曝光图像融合

Exposure-Aware Dynamic Weighted Learning for Single-Shot HDR Imaging

• Paper:
• Code: https://github.com/viengiaan/EDWL

Ghost-free High Dynamic Range Imaging with Context-aware Transformer

• Paper: https://arxiv.org/abs/2208.05114
• Code: https://github.com/megvii-research/HDR-Transformer

HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fields

• Paper: https://arxiv.org/abs/2208.06787
• Code: https://github.com/postech-ami/HDR-Plenoxels

Frame Interpolation - 插帧

Real-Time Intermediate Flow Estimation for Video Frame Interpolation

• Paper: https://arxiv.org/abs/2011.06294
• Code: https://github.com/hzwer/ECCV2022-RIFE

FILM: Frame Interpolation for Large Motion

• Paper: https://arxiv.org/abs/2202.04901
• Code: https://github.com/google-research/frame-interpolation

Video Interpolation by Event-driven Anisotropic Adjustment of Optical Flow

• Paper: https://arxiv.org/abs/2208.09127

Spatial-Temporal Video Super-Resolution

Towards Interpretable Video Super-Resolution via Alternating Optimization

• Paper: https://arxiv.org/abs/2207.10765
• Code: https://github.com/caojiezhang/DAVSR

Image Enhancement - 图像增强

Local Color Distributions Prior for Image Enhancement

• Paper: https://www.cs.cityu.edu.hk/~rynson/papers/eccv22b.pdf
• Code: https://github.com/hywang99/LCDPNet

SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancement

• Paper: https://arxiv.org/abs/2207.08351

Neural Color Operators for Sequential Image Retouching

• Paper: https://arxiv.org/abs/2207.08080
• Code: https://github.com/amberwangyili/neurop

Unsupervised Night Image Enhancement: When Layer Decomposition Meets Light-Effects Suppression

• Paper: https://arxiv.org/abs/2207.10564
• Code: https://github.com/jinyeying/night-enhancement

Low-Light Image Enhancement

LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

• Paper: https://arxiv.org/abs/2202.03373
• Code: https://github.com/sczhou/LEDNet

Image Harmonization - 图像协调

Harmonizer: Learning to Perform White-Box Image and Video Harmonization

• Paper: https://arxiv.org/abs/2207.01322
• Code: https://github.com/ZHKKKe/Harmonizer

DCCF: Deep Comprehensible Color Filter Learning Framework for High-Resolution Image Harmonization

• Paper: https://arxiv.org/abs/2207.04788
• Code: https://github.com/rockeyben/DCCF

Image Completion/Inpainting - 图像修复

Learning Prior Feature and Attention Enhanced Image Inpainting

• Paper: https://arxiv.org/abs/2208.01837
• Code: https://github.com/ewrfcas/MAE-FAR

Perceptual Artifacts Localization for Inpainting

• Paper: https://arxiv.org/abs/2208.03357
• Code: https://github.com/owenzlz/PAL4Inpaint

Video Inpainting

Error Compensation Framework for Flow-Guided Video Inpainting

• Paper: https://arxiv.org/abs/2207.10391

Flow-Guided Transformer for Video Inpainting

• Paper: https://arxiv.org/abs/2208.06768
• Code: https://github.com/hitachinsk/FGT

Image Colorization - 图像上色

Eliminating Gradient Conflict in Reference-based Line-art Colorization

• Paper: https://arxiv.org/abs/2207.06095
• Code: https://github.com/kunkun0w0/SGA

Bridging the Domain Gap towards Generalization in Automatic Colorization

• Paper:
• Code: https://github.com/Lhyejin/DG-Colorization

Image Matting - 图像抠图

TransMatting: Enhancing Transparent Objects Matting with Transformers

• Paper: https://arxiv.org/abs/2208.03007
• Code: https://github.com/AceCHQ/TransMatting

One-Trimap Video Matting

• Paper: https://arxiv.org/abs/2207.13353
• Code: https://github.com/Hongje/OTVM

Shadow Removal - 阴影消除

Style-Guided Shadow Removal

• Paper:
• Code: https://github.com/jinwan1994/SG-ShadowNet

Image Compression - 图像压缩

Optimizing Image Compression via Joint Learning with Denoising

• Paper: https://arxiv.org/abs/2207.10869
• Code: https://github.com/felixcheng97/DenoiseCompression

Implicit Neural Representations for Image Compression

• Paper: https://arxiv.org/abs/2112.04267
• Code：https://github.com/YannickStruempler/inr_based_compression

Expanded Adaptive Scaling Normalization for End to End Image Compression

• Paper: https://arxiv.org/abs/2208.03049

Content-Oriented Learned Image Compression

• Paper:
• Code: https://github.com/lmijydyb/COLIC

Video Compression

AlphaVC: High-Performance and Efficient Learned Video Compression

• Paper: https://arxiv.org/abs/2207.14678

Image Quality Assessment - 图像质量评价

FAST-VQA: Efficient End-to-end Video Quality Assessment with Fragment Sampling

• Paper: https://arxiv.org/abs/2207.02595
• Code: https://github.com/TimothyHTimothy/FAST-VQA

Shift-tolerant Perceptual Similarity Metric

• Paper: https://arxiv.org/abs/2207.13686
• Code: https://github.com/abhijay9/ShiftTolerant-LPIPS/

Telepresence Video Quality Assessment

• Paper: https://arxiv.org/abs/2207.09956

Style Transfer - 风格迁移

CCPL: Contrastive Coherence Preserving Loss for Versatile Style Transfer

• Paper: https://arxiv.org/abs/2207.04808
• Code: https://github.com/JarrentWu1031/CCPL

Image-Based CLIP-Guided Essence Transfer

• Paper: https://arxiv.org/abs/2110.12427
• Code: https://github.com/hila-chefer/TargetCLIP

Learning Graph Neural Networks for Image Style Transfer

• Paper: https://arxiv.org/abs/2207.11681

WISE: Whitebox Image Stylization by Example-based Learning

• Paper: https://arxiv.org/abs/2207.14606
• Code: https://github.com/winfried-loetzsch/wise

Image Editing - 图像编辑

Context-Consistent Semantic Image Editing with Style-Preserved Modulation

• Paper: https://arxiv.org/abs/2207.06252
• Code: https://github.com/WuyangLuo/SPMPGAN

GAN with Multivariate Disentangling for Controllable Hair Editing

• Paper: https://raw.githubusercontent.com/XuyangGuo/xuyangguo.github.io/main/database/CtrlHair/CtrlHair.pdf
• Code: https://github.com/XuyangGuo/CtrlHair

Paint2Pix: Interactive Painting based Progressive Image Synthesis and Editing

• Paper: https://arxiv.org/abs/2208.08092
• Code: https://github.com/1jsingh/paint2pix

High-fidelity GAN Inversion with Padding Space

• Paper: https://arxiv.org/abs/2203.11105
• Code: https://github.com/EzioBy/padinv

Text2LIVE: Text-Driven Layered Image and Video Editing

• Paper: https://arxiv.org/abs/2204.02491
• Code: https://github.com/omerbt/Text2LIVE

Image Generation/Synthesis / Image-to-Image Translation - 图像生成/合成/转换

TIPS: Text-Induced Pose Synthesis

• Paper: https://arxiv.org/abs/2207.11718
• Code: https://github.com/prasunroy/tips

TISE: A Toolbox for Text-to-Image Synthesis Evaluation

• Paper: https://arxiv.org/abs/2112.01398
• Code: https://github.com/VinAIResearch/tise-toolbox

Learning Visual Styles from Audio-Visual Associations

• Paper: https://arxiv.org/abs/2205.05072
• Code: https://github.com/Tinglok/avstyle

End-to-end Graph-constrained Vectorized Floorplan Generation with Panoptic Refinement

• Paper: https://arxiv.org/abs/2207.13268

ManiFest: Manifold Deformation for Few-shot Image Translation

• Paper: https://arxiv.org/abs/2111.13681
• Code: https://github.com/cv-rits/ManiFest

VecGAN: Image-to-Image Translation with Interpretable Latent Directions

• Paper: https://arxiv.org/abs/2207.03411

DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation

• Paper: https://arxiv.org/abs/2207.06124
• Code: https://github.com/Huage001/DynaST

Cross Attention Based Style Distribution for Controllable Person Image Synthesis

• Paper: https://arxiv.org/abs/2208.00712
• Code: https://github.com/xyzhouo/CASD

EleGANt: Exquisite and Locally Editable GAN for Makeup Transfer

• Paper: https://arxiv.org/abs/2207.09840
• Code: https://github.com/Chenyu-Yang-2000/EleGANt

Vector Quantized Image-to-Image Translation

• Paper: https://arxiv.org/abs/2207.13286
• Code: https://github.com/cyj407/VQ-I2I

URUST: Ultra-high-resolution unpaired stain transformation via Kernelized Instance Normalization

• Paper: https://arxiv.org/abs/2208.10730
• Code: https://github.com/Kaminyou/URUST

General Object Pose Transformation Network from Unpaired Data

• Paper:
• Code: https://github.com/suyukun666/UFO-PT

Style Your Hair: Latent Optimization for Pose-Invariant Hairstyle Transfer via Local-Style-Aware Hair Alignment

• Paper: https://arxiv.org/abs/2208.07765
• Code: https://github.com/Taeu/Style-Your-Hair

StyleLight: HDR Panorama Generation for Lighting Estimation and Editing

• Paper: https://arxiv.org/abs/2207.14811
• Code: https://github.com/Wanggcong/StyleLight

Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling

• Paper: https://arxiv.org/abs/2207.02196
• Code: https://github.com/fudan-zvg/PDS

GAN Cocktail: mixing GANs without dataset access

• Paper: https://arxiv.org/abs/2106.03847
• Code: https://github.com/omriav/GAN-cocktail

Compositional Visual Generation with Composable Diffusion Models

• Paper: https://arxiv.org/abs/2206.01714
• Code: https://github.com/energy-based-model/Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch

Adaptive-Feature-Interpolation-for-Low-Shot-Image-Generation

• Paper: https://arxiv.org/abs/2112.02450
• Code: https://github.com/dzld00/Adaptive-Feature-Interpolation-for-Low-Shot-Image-Generation

StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pretrained StyleGAN

• Paper: https://arxiv.org/abs/2203.04036
• Code: https://github.com/FeiiYin/StyleHEAT

WaveGAN: An Frequency-aware GAN for High-Fidelity Few-shot Image Generation

• Paper: https://arxiv.org/abs/2207.07288
• Code: https://github.com/kobeshegu/ECCV2022_WaveGAN

Supervised Attribute Information Removal and Reconstruction for Image Manipulation

• Paper: https://arxiv.org/abs/2207.06555
• Code: https://github.com/NannanLi999/AIRR

FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs

• Paper: https://arxiv.org/abs/2207.08630
• Code: https://github.com/iceli1007/FakeCLR

Auto-regressive Image Synthesis with Integrated Quantization

• Paper: https://arxiv.org/abs/2207.10776
• Code: https://github.com/fnzhan/IQ-VAE

PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation

• Paper: https://arxiv.org/abs/2204.00833
• Code: https://github.com/BlingHe/PixelFolder

DeltaGAN: Towards Diverse Few-shot Image Generation with Sample-Specific Delta

• Paper: https://arxiv.org/abs/2207.10271
• Code: https://github.com/bcmi/DeltaGAN-Few-Shot-Image-Generation

Generator Knows What Discriminator Should Learn in Unconditional GANs

• Paper: https://arxiv.org/abs/2207.13320
• Code: https://github.com/naver-ai/GGDR

Hierarchical Semantic Regularization of Latent Spaces in StyleGANs

• Paper: https://arxiv.org/abs/2208.03764
• Code: https://drive.google.com/file/d/1gzHTYTgGBUlDWyN_Z3ORofisQrHChg_n/view

FurryGAN: High Quality Foreground-aware Image Synthesis

• Paper: https://arxiv.org/abs/2208.10422
• Project: https://jeongminb.github.io/FurryGAN/

Improving GANs for Long-Tailed Data through Group Spectral Regularization

• Paper: https://arxiv.org/abs/2208.09932
• Code: https://drive.google.com/file/d/1aG48i04Q8mOmD968PAgwEvPsw1zcS4Gk/view

Video Generation

Long Video Generation with Time-Agnostic VQGAN and Time-Sensitive Transformer

• Paper: https://arxiv.org/abs/2204.03638
• Code: https://github.com/SongweiGe/TATS

Controllable Video Generation through Global and Local Motion Dynamics

• Paper: https://arxiv.org/abs/2204.06558
• Code: https://github.com/Araachie/glass

Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis

• Paper: https://arxiv.org/abs/2207.05049
• Code: https://github.com/fast-vid2vid/fast-vid2vid

Synthesizing Light Field Video from Monocular Video

• Paper: https://arxiv.org/abs/2207.10357
• Code: https://github.com/ShrisudhanG/Synthesizing-Light-Field-Video-from-Monocular-Video

Others

Learning Local Implicit Fourier Representation for Image Warping

• Paper: https://ipl.dgist.ac.kr/LTEW.pdf
• Code: https://github.com/jaewon-lee-b/ltew
• Tags: Image Warping

Dress Code: High-Resolution Multi-Category Virtual Try-On

• Paper: https://arxiv.org/abs/2204.08532
• Code: https://github.com/aimagelab/dress-code
• Tags: Virtual Try-On

High-Resolution Virtual Try-On with Misalignment and Occlusion-Handled Conditions

• Paper: https://arxiv.org/abs/2206.14180
• Code: https://github.com/sangyun884/HR-VITON
• Tags: Virtual Try-On

Single Stage Virtual Try-on via Deformable Attention Flows

• Paper: https://arxiv.org/abs/2207.09161
• Tags: Virtual Try-On

Outpainting by Queries

• Paper: https://arxiv.org/abs/2207.05312
• Code: https://github.com/Kaiseem/QueryOTR
• Tags: Outpainting

Geometry-aware Single-image Full-body Human Relighting

• Paper: https://arxiv.org/abs/2207.04750

NeRF for Outdoor Scene Relighting

• Paper: https://arxiv.org/abs/2112.05140
• Code: https://github.com/r00tman/NeRF-OSR

Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal

• Paper: https://arxiv.org/abs/2207.08178
• Code: https://github.com/thinwayliu/Watermark-Vaccine
• Tags: Watermark Protection

Efficient Meta-Tuning for Content-aware Neural Video Delivery

• Paper: https://arxiv.org/abs/2207.09691
• Code: https://github.com/Neural-video-delivery/EMT-Pytorch-ECCV2022
• Tags: Video Delivery

Human-centric Image Cropping with Partition-aware and Content-preserving Features

• Paper: https://arxiv.org/abs/2207.10269
• Code: https://github.com/bcmi/Human-Centric-Image-Cropping

CelebV-HQ: A Large-Scale Video Facial Attributes Dataset

• Paper: https://arxiv.org/abs/2207.12393
• Code: https://github.com/CelebV-HQ/CelebV-HQ
• Tags: Dataset

Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesis

• Paper: https://arxiv.org/abs/2207.11770
• Code: https://github.com/sstzal/DFRF
• Tags: Talking Head Synthesis

Contrastive Monotonic Pixel-Level Modulation

• Paper: https://arxiv.org/abs/2207.11517
• Code: https://github.com/lukun199/MonoPix

AutoTransition: Learning to Recommend Video Transition Effects

• Paper: https://arxiv.org/abs/2207.13479
• Code: https://github.com/acherstyx/AutoTransition

Bringing Rolling Shutter Images Alive with Dual Reversed Distortion

• Paper: https://arxiv.org/abs/2203.06451
• Code: https://github.com/zzh-tech/Dual-Reversed-RS

Learning Object Placement via Dual-path Graph Completion

• Paper: https://arxiv.org/abs/2207.11464
• Code: https://github.com/bcmi/GracoNet-Object-Placement

DeepMCBM: A Deep Moving-camera Background Model

• Paper:
• Code: https://github.com/BGU-CS-VIL/DeepMCBM

Mind the Gap in Distilling StyleGANs

• Paper: https://arxiv.org/abs/2208.08840
• Code: https://github.com/xuguodong03/StyleKD