pinglmlcv

Adversarial-attack-on-Person-ReID-With-Deep-Mis-Ranking

This is a pytorch implementation of the CVPR2020 paper: Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking

BA3US

code for our ECCV 2020 paper "A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation"

BiSIDA

Code for "Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation" accepted by AAAI-2021.

Black-box-Adversarial-Reprogramming

Code for "Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources". (ICML 2020)

causal-ml

Must-read papers and resources related to causal inference and machine (deep) learning

CLADE

Semantic Image Synthesis via Efficient Class-Adaptive Normalization

CNAS

Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search

DANCE

repository for Universal Domain Adaptation through Self-supervision

EAGRNet

Edge-aware Graph Representation Learning and Reasoning for Face Parsing (ECCV 2020)

FADA

(ECCV 2020) Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation

FedNova

PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.

FFD_CVPR2020

GraphCL

[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

IFVD

Intra-class Feature Variation Distillation for Semantic Segmentation (ECCV 2020)

InfoGraph

Official code for ICLR spotlight paper "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization"

label-distillation

Official PyTorch implementation of “Flexible Dataset Distillation: Learn Labels Instead of Images”

margin-openset

[ICCV2019] Attract or Distract: Exploit the Margin of Open Set

multi-source-attention

Multi-Source Domain Attention

NAS-DIP-pytorch

[ECCV 2020] NAS-DIP: Learning Deep Image Prior with Neural Architecture Search

PLMpapers

Must-read Papers on pre-trained language models.

PyTorch-StudioGAN

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

SemanticAdv

SHOT

code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

TSIT

[ECCV 2020 Spotlight] A Simple and Versatile Framework for Image-to-Image Translation

TTSR

[CVPR'20] TTSR: Learning Texture Transformer Network for Image Super-Resolution

VILLA

Research Code for NeurIPS 2020 Spotlight paper "Large-Scale Adversarial Training for Vision-and-Language Representation Learning": UNITER adversarial training part

VisionLearningGroup.github.io

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

VL-BERT

Code for ICLR 2020 paper "VL-BERT: Pre-training of Generic Visual-Linguistic Representations".

XingGAN

[ECCV 2020] XingGAN for Person Image Generation