WeitaoVan
Ph.D. graduated at 2021 from EE, Tsinghua University. My research interests include object detection/tracking/segmentation and adversarial examples.
Tsinghua UniversityBeijing, China
Pinned Repositories
CV
faceID
Caffe Implementation of our ICIP 2017 paper OCCLUSION ROBUST FACE RECOGNITION BASED ON MASK LEARNING
feishu-chatgpt
Feishu-OpenAI
🎒 飞书 ×(GPT-4 + DALL·E + Whisper)= 飞一般的工作体验 🚀 语音对话、角色扮演、多话题讨论、图片创作、表格分析、文档导出 🚀
L-GM-loss
Implementation of our accepted CVPR 2018 paper "Rethinking Feature Distribution for Loss Functions in Image Classification"
mean-teacher
A state-of-the-art semi-supervised method for image recognition
Sohu-LuckData-Image-Text-Matching-Competition
Sohu 2017 competition. We won the third prize.
SS-NAN
keras implement of the paper Self-Supervised Neural Aggregation Networks for Human Parsing
vat
Code for reproducing the results on the MNIST dataset in the paper "Distributional Smoothing with Virtual Adversarial Training"
WeitaoVan.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
WeitaoVan's Repositories
WeitaoVan/L-GM-loss
Implementation of our accepted CVPR 2018 paper "Rethinking Feature Distribution for Loss Functions in Image Classification"
WeitaoVan/faceID
Caffe Implementation of our ICIP 2017 paper OCCLUSION ROBUST FACE RECOGNITION BASED ON MASK LEARNING
WeitaoVan/Sohu-LuckData-Image-Text-Matching-Competition
Sohu 2017 competition. We won the third prize.
WeitaoVan/mean-teacher
A state-of-the-art semi-supervised method for image recognition
WeitaoVan/CV
WeitaoVan/feishu-chatgpt
WeitaoVan/Feishu-OpenAI
🎒 飞书 ×(GPT-4 + DALL·E + Whisper)= 飞一般的工作体验 🚀 语音对话、角色扮演、多话题讨论、图片创作、表格分析、文档导出 🚀
WeitaoVan/SS-NAN
keras implement of the paper Self-Supervised Neural Aggregation Networks for Human Parsing
WeitaoVan/vat
Code for reproducing the results on the MNIST dataset in the paper "Distributional Smoothing with Virtual Adversarial Training"
WeitaoVan/WeitaoVan.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes