Pinned Repositories
Awesome-Super-Resolution
Collect super-resolution related papers, data, repositories
AWSRN
PyTorch code for our paper "Lightweight Image Super-Resolution with Adaptive Weighted Learning Network"
bcnn
caffe
Caffe on both Linux and Windows
DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为15个章节，近20万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
L-GM_loss_pytorch
Rethinking Feature Distribution for Loss Functions in Image Classification
MobileSAM
This is the offiicial code for Faster Segment Anything (MobileSAM) project that makes SAM lightweight
Npair_loss_pytorch
Improved Deep Metric Learning with Multi-class N-pair Loss Objective
Paper_Reading_List
Recommended Papers. Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Learning (cs.LG)
yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
ChaofWang's Repositories
ChaofWang/Awesome-Super-Resolution
Collect super-resolution related papers, data, repositories
ChaofWang/AWSRN
PyTorch code for our paper "Lightweight Image Super-Resolution with Adaptive Weighted Learning Network"
ChaofWang/Npair_loss_pytorch
Improved Deep Metric Learning with Multi-class N-pair Loss Objective
ChaofWang/L-GM_loss_pytorch
Rethinking Feature Distribution for Loss Functions in Image Classification
ChaofWang/DeepLearning-500-questions
深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为15个章节，近20万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06
ChaofWang/Paper_Reading_List
Recommended Papers. Subjects: Computer Vision and Pattern Recognition (cs.CV); Artificial Intelligence (cs.AI); Learning (cs.LG)
ChaofWang/bcnn
ChaofWang/caffe
Caffe on both Linux and Windows
ChaofWang/MobileSAM
This is the offiicial code for Faster Segment Anything (MobileSAM) project that makes SAM lightweight
ChaofWang/netscope
Neural network visualizer
ChaofWang/PIL
ImageProcess opencv+QT
ChaofWang/ResNeSt
ResNeSt: Split-Attention Network
ChaofWang/simple-faster-rcnn-pytorch
A simplified implemention of Faster R-CNN that replicate performance from origin paper
ChaofWang/yolov5
YOLOv5 in PyTorch > ONNX > CoreML > TFLite