Pinned Repositories
AdvSemiSeg
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
Caffe-DeepLab-v2-Reduced
The DeepLab-v2 caffe with CUDA 6.0 compatibility and reduced memory for FCN.
cmr
Project repo for Learning Category-Specific Mesh Reconstruction from Image Collections
cunn-SpatialNLLCriterionwithMask
GCPNet
Scene Parsing with Global Context Embedding, ICCV 2017
hfslyc.github.io
Wei-Chih Wayne Hung's personal website
LearnToBlend
"Learning To Blend Photos," ECCV 2018
FAVOS
Demo code of the paper "Fast and Accurate Online Video Object Segmentation via Tracking Parts", in CVPR 2018
SCOPS
SCOPS: Self-Supervised Co-Part Segmentation (CVPR'19)
AdaptSegNet
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
hfslyc's Repositories
hfslyc/AdvSemiSeg
Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018
hfslyc/LearnToBlend
"Learning To Blend Photos," ECCV 2018
hfslyc/GCPNet
Scene Parsing with Global Context Embedding, ICCV 2017
hfslyc/Caffe-DeepLab-v2-Reduced
The DeepLab-v2 caffe with CUDA 6.0 compatibility and reduced memory for FCN.
hfslyc/hfslyc.github.io
Wei-Chih Wayne Hung's personal website
hfslyc/cmr
Project repo for Learning Category-Specific Mesh Reconstruction from Image Collections
hfslyc/cunn-SpatialNLLCriterionwithMask
hfslyc/fast-rcnn
Fast R-CNN
hfslyc/FeatureLearning
FeatureLearning-ECCV2016
hfslyc/FPN_Pytorch
Base jwyang/fpn.pytorch, train FPN on Pascal VOC get 80.5 mAP
hfslyc/nn-SpatialNLLCriterionwithMask
hfslyc/openalpr
Automatic License Plate Recognition library
hfslyc/pytorch-a2c-ppo-acktr
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO) and Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR).
hfslyc/pytorch-faster-rcnn
hfslyc/SCOPS
SCOPS: Self-Supervised Co-Part Segmentation (CVPR'19)
hfslyc/torch-distro-SpatialNLLCriterionwithMask
Torch installation in a self-contained folder
hfslyc/tracking_wo_bnw
Implementation of "Tracking without bells and whistles” and the multi-object tracking "Tracktor"