Wayne's starred repositories
collaborative-experts
Video embeddings for retrieval with natural language queries
Awesome_Matching_Pretraining_Transfering
The Paper List of Large Multi-Modality Model, Parameter-Efficient Finetuning, Vision-Language Pretraining, Conventional Image-Text Matching for Preliminary Insight.
semantic_neighborhoods
Preserving Semantic Neighborhoods for Robust Cross-modal Retrieval [ECCV 2020]
retrieval.pytorch
Adaptive Cross-Modal Embeddings for Image-Sentence Alignment
dml_cross_entropy
Code for the paper "A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses" (ECCV 2020 - Spotlight)
SupContrast
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
group_loss
Official code for "The Group Loss for Deep Metric Learning" paper (ECCV 2020)
meta-weight-net
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
byol-pytorch
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
awesome-contrastive-self-supervised-learning
A comprehensive list of awesome contrastive self-supervised learning papers.
awesome-multimodal-ml
Reading list for research topics in multimodal machine learning
Revisiting_Deep_Metric_Learning_PyTorch
(ICML 2020) This repo contains code for our paper "Revisiting Training Strategies and Generalization Performance in Deep Metric Learning" (https://arxiv.org/abs/2002.08473) to facilitate consistent research in the field of Deep Metric Learning.
ECCV2020_DiVA_MultiFeature_DML
(ECCV 2020) This repo contains code for "DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning" (https://arxiv.org/abs/2004.13458), which extends vanilla DML with auxiliary and self-supervised features.
embedding-expansion
Official MXNet implementation of "Embedding Expansion: Augmentation in Embedding Space for Deep Metric Learning" (CVPR 2020)
ECCV2020_DiVA_MultiFeature_DML
(ECCV 2020) This repo contains code for "DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning" (https://arxiv.org/abs/2004.13458), which extends vanilla DML with auxiliary and self-supervised features.