Official PyTorch Implementation of paper "Vision Transformer for NeRF-Based View Synthesis from a Single Input Image", WACV 2023.

[CVPR 2020] Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline

[CVPR 2020] Learning to See Through Obstructions

Download market data from Yahoo! Finance's API

Depth-Aware Video Frame Interpolation (CVPR 2019)

MSGAN: Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis (CVPR2019)

Adversarial Learning for Semi-supervised Semantic Segmentation, BMVC 2018

Convolutional Spatial Propagation Network

Deep Semantic Face Deblurring

[ECCV 2018] DF-Net: Unsupervised Joint Learning of Depth and Flow using Cross-Task Consistency

TensorFlow implementation of the CVPR 2018 spotlight paper, Deep Photo Enhancer: Unpaired Learning for Image Enhancement from Photographs with GANs

Learning diverse image-to-image translation from unpaired data

"Learning To Blend Photos," ECCV 2018

PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume, CVPR 2018 (Oral)

code for "Fast Patch-based Style Transfer of Arbitrary Style".

Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration

Photorealistic Style Transfer with Screened Poisson Equation

Pytorch and Torch testing code of CartoonGAN [Chen et al., CVPR18]

Official Implementation of Fast End-to-End Trainable Guided Filter, CVPR 2018

This is a personal reimplementation of Phase-Based Frame Interpolation for Video [Meyer et al. 2015]

PyTorch implementations of Generative Adversarial Networks.

Code for the paper "A Comparative Study of Algorithms for Realtime Panoramic Video Blending"

DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral

Official Chainer implementation of GP-GAN: Towards Realistic High-Resolution Image Blending (ACMMM 2019, oral)

The project is an official implement of our CVPR2018 paper "Deep Back-Projection Networks for Super-Resolution" (Winner of NTIRE2018 and PIRM2018)

Progressive Growing of GANs for Improved Quality, Stability, and Variation

Video style transfer using feed-forward networks.

Code for the paper 'Globally and Locally Consistent Image Completion'. http://iizuka.cs.tsukuba.ac.jp/projects/completion/

Torch implementation for the paper "Artistic style transfer for videos"