Name: vv
Type: User
Company: University of Electronic Science and Technology of China
Bio: I'm pursuing a Ph.D. degree in the SCSE, UESTC. My research interests include spiking neural networks, lightweight neural networks, and efficient deep learning.
Location: Chengdu, Sichuan Province, China
Blog: https://scholar.google.com.hk/citations?user=OIZR2YYAAAAJ&hl=zh-CN
vv's Projects
Awasome Papers and Resources in Deep Neural Network Pruning with Source Code.
A list of papers, docs, codes about efficient AIGC. This repo is aimed to provide the info for efficient AIGC research, including language and vision, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.
A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.
A curated list of neural network pruning resources.
List of papers related to neural network quantization in recent AI conferences and journals.
🔥 This repo collects summit papers, codes about Spiking Neural Networks for anyone who wants to do research on it. We are continuously improving the project.
A paper list of spiking neural networks, including papers, codes, and related websites.
⏰ Collaboratively track deadlines of conferences recommended by CCF (Website, Python Cli, Wechat Applet) / If you find it useful, please star this project, thanks~
Event-based camera data representation and processing. Some common representations and reference codes.
整理国内事件相机研究团队。逐步整理
Advancing Spiking Neural Networks towards Deep Residual Learning
(2020-2022)The PyTorch version of SiamFC,SiamRPN,DaSiamRPN, UpdateNet , SiamDW, SiamRPN++, SiamMask, SiamFC++, SiamCAR, SiamBAN, Ocean, LightTrack , TrTr, NanoTrack; Visual object tracking based on deep learning
Paper list for single object tracking (State-of-the-art SOT trackers)
Update arXiv papers about Spiking Neural Networks daily.
The collection of training tricks of binarized neural networks.