JunlinHan's starred repositories
anycost-gan
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
Robust-Color-Guided-Depth-Map-Restoration
Liu, W., Chen, X., Yang, J., & Wu, Q. (2017). Robust color guided depth map restoration. IEEE Transactions on Image Processing, 26(1), 315-327.
Semi-Global-Weighted-Least-Squares-in-Image-Filtering
This is the released code for the following paper: "Semi-global weighted least squares in image filtering.", Wei Liu, Xiaogang Chen, Chuanhua Shen, Zhi Liu, and Jie Yang. In ICCV 2017.
Comparison-of-Disparity-Estimation-Algorithms
Implementation of simple block matching, block matching with dynamic programming and Stereo Matching using Belief Propagation algorithm for stereo disparity estimation
FPN-Semantic-segmentation
use FPN to FPN-Semantic-segmentation。pytorch version
Graduate_Application
Documents used for grad school application
stargan-v2
StarGAN v2 - Official PyTorch Implementation (CVPR 2020)
stylegan2-pytorch
Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement
stylegan2-pytorch
Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch
stylegan2-colab
StyleGAN2 - Colab Notebook containing code for training + visualization + projection
D2HC-RMVSNet
The official repository of the paper "Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking" (ECCV2020 Spotlight)
X-StereoLab
SOS IROS 2018 GOOGLE; StereoNet ECCV2018 GOOGLE; ActiveStereoNet ECCV2018 Oral GOOGLE; HITNET CVPR2021 GOOGLE;PLUME Uber ATG
consistent_depth
We estimate dense, flicker-free, geometrically consistent depth from monocular video, for example hand-held cell phone video.
pwc-net.pytorch
Off-the-shelf PWC-Net module in PyTorch-1.0+
image-to-image-papers
🦓<->🦒 🌃<->🌆 A collection of image to image papers with code (constantly updating)
taming-transformers
Taming Transformers for High-Resolution Image Synthesis
FlowNetPytorch
Pytorch implementation of FlowNet by Dosovitskiy et al.