[ECCV 2024] Official PyTorch implementation of RoPE-ViT "Rotary Position Embedding for Vision Transformer"

CVPR 2024 Highlight: Frequency-Adaptive Dilated Convolution for Semantic Segmentation

🚀 Efficient implementations of state-of-the-art linear attention models in Pytorch and Triton

We write your reusable computer vision tools. 💜

[NeurIPS 2024 spotlight] Offical implementation of MSFA and release of SARDet_100K dataset for Large-Scale Synthetic Aperture Radar (SAR) Object Detection

Replacing Mamba with xLSTM! It works better. We show that xLSTM-Unet can be an effective semantic segmentation backbone.

Image registration algorithm. Includes SIFT, SAR-SIFT,PSO-SIFT.

《动手学大模型Dive into LLMs》系列编程实践教程

Combining Graph Neural Network and Mamba to Capture Local and Global Tissue Spatial Relationships in Whole Slide Images

[Mamba-Survey-2024] Paper list for State-Space-Model/Mamba and it's Applications

Graph-Mamba: Towards Long-Range Graph Sequence Modelling with Selective State Spaces

Mamba SSM architecture

期刊分区查询小工具，包括中科院分区表升级版（2023、2022、2021）及国际期刊预警名单（2024、2023、2021、2020）、JCR（2023、2022、2021、2020）、CCF推荐国际会议和期刊目录（2022）、计算领域高质量科技期刊分级目录（2022）。

A list for GNNs and related works.

✨✨Latest Papers on Vision Mamba and Related Areas

Collect papers about Mamba (a selective state space model).

Official implementation of paper "Knowledge Distillation from A Stronger Teacher", NeurIPS 2022

[CVPR-2022] Official implementation for "Knowledge Distillation with the Reused Teacher Classifier".

Multiple domain characteristics joint learning of SAR targets for SAR-ATR

Official repository for the paper "Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting" (TPAMI'22) https://arxiv.org/abs/2006.09252

Xidian University TeX Suite 西安电子科技大学LaTeX套装

A high-level toolbox for using complex valued neural networks in PyTorch

Collect some papers about transformer with vision. Awesome Transformer with Computer Vision (CV)

Official Pytorch code for Structure-Aware Transformer.

Representing Long-Range Context for Graph Neural Networks with Global Attention

Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.

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

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).