FutureTwT

PyTorch-Geometric-Study

关于Pytorch-Geometric的学习，包括官方文档的基本内容和部分API的使用方式，以及官方源码中的示例代码和Pytorch-Geometric的部分源码实现

BSTH

The source code of "Bit-aware Semantic Transformer Hashing for Multi-modal Retrieval." (Accepted by SIGIR 2022)

HMAH

The source code of "Teacher-Student Learning: Efficient Hierarchical Message Aggregation Hashing for Cross-Modal Retrieval." (Accepted by TMM 2022)

NCH

The source code of "Partial Multi-Modal Hashing via Neighbor-aware Completion Learning." (Accepted by TMM 2023)

Code-Reading

Reading the code of papers.

Paper-Reading

Take notes on the paper reading

Cross-Modal-Hashing-Retrieval

The baselines of cross-modal hashing retrieval.

FutureTwT

Config files for my GitHub profile.

hashing-baseline-for-image-retrieval

:octocat:Various hashing methods for image retrieval and serves as the baselines

Optimizer

最优化理论实现：（1）单纯性算法（2）运输问题

Awesome-Incremental-Learning

Awesome Incremental Learning

Best-Incremental-Learning

An Incremental Learning, Continual Learning, and Life-Long Learning Repository

Cross-modal_Retrieval_Tutorial

The Paper List of Image-Text Matching for Preliminary Insight.

DBSTH

FutureTwT.github.io

My academic personal website.

github-profile-summary-cards-example

github-profile-summary-cards' template

Image-Hashing-Baselines

Collect some deep image hashing methods and integrate them into my own baselines.

LAGNH

Two-pronged Strategy: Lightweight Augmented Graph Network Hashing for Scalable Image Retrieval (MM 2021)

Multi-Modal-Hashing-Retrieval

The baselines of multi-modal hashing retrieval.

pytorch-loss

label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

YUN-2020

基于多种机器学习模型与深度学习模型的评论文本分类(Reconstruct the old YUN project.)