[CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning
This is a pytorch implementation of the CVPR2020 paper: Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking
Code for the paper: Adversarial Training against Location-Optimized Adversarial Patches. ECCV CVCOPS 2020 (to appear)
code for our ECCV 2020 paper "A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation"
Must-read papers and resources related to causal inference and machine (deep) learning
Semantic Image Synthesis via Efficient Class-Adaptive Normalization
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
repository for Universal Domain Adaptation through Self-supervision
Densely Connected Search Space for More Flexible Neural Architecture Search (CVPR2020)
Edge-aware Graph Representation Learning and Reasoning for Face Parsing (ECCV 2020)
(ECCV 2020) Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.
[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen
Guided Image-to-Image Translation Papers
Intra-class Feature Variation Distillation for Semantic Segmentation (ECCV 2020)
Official code for ICLR spotlight paper "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization"
Official PyTorch implementation of “Flexible Dataset Distillation: Learn Labels Instead of Images”
Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020).
Multi-Source Domain Attention
[ECCV 2020] NAS-DIP: Learning Deep Image Prior with Neural Architecture Search
Code for Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells, CVPR '19
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Research Code for NeurIPS 2020 Spotlight paper "Large-Scale Adversarial Training for Vision-and-Language Representation Learning": UNITER adversarial training part
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Code for ICLR 2020 paper "VL-BERT: Pre-training of Generic Visual-Linguistic Representations".
[ECCV 2020] XingGAN for Person Image Generation