ARC Lab, Tencent PCG
ARC Lab, Tencent PCG
GFPGAN
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
AnimeSR
Codes for "AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos"
Efficient-VSR-Training
Codes for "Accelerating the Training of Video Super-Resolution"
FAIG
NeurIPS 2021, Spotlight, Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
MCQ
Official code for "Bridging Video-text Retrieval with Multiple Choice Questions", CVPR 2022 (Oral).
MM-RealSR
Codes for "Metric Learning based Interactive Modulation for Real-World Super-Resolution"
RepSR
Codes for "RepSR: Training Efficient VGG-style Super-Resolution Networks with Structural Re-Parameterization and Batch Normalization"
UMT
UMT is a unified and flexible framework which can handle different input modality combinations, and output video moment retrieval and/or highlight detection results.
VQFR
ECCV 2022, Oral, VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder
DTN
Official code for "Dynamic Token Normalization Improves Vision Transformer", ICLR 2022.