Unofficial PyTorch code for BasicVSR

Overview

Dependencies and Installation

  • The code is based on BasicSR, Please install the BasicSR framework first.
  • Pytorch=1.51

Training

cd ./code

CUDA_VISIBLE_DEVICES=0,1 python basicsr/train.py -opt options/train/BasicVSR/train_BasicVSR.yml

CUDA_VISIBLE_DEVICES=0,1 python basicsr/train.py -opt options/train/BasicVSR/train_IconVSR.yml

Testing

cd ./code

CUDA_VISIBLE_DEVICES=0 python basicsr/test.py -opt options/test/BasicVSR/test_BasicVSR_REDS.yml

CUDA_VISIBLE_DEVICES=0 python basicsr/test.py -opt options/test/BasicVSR/test_BasicVSR_Vid4.yml

PSNR/SSIM Results

It takes about 5 days to train the BasicVSR/IconVSR model with the REDS dataset on 2 V100 GPUs.

Dataset(BI) BasicVSR (paper) Ours IconVSR_w/o Refill (paper) Ours
REDS4 31.42/0.8909 31.409/0.8907 31.60 31.6026
Vid4 27.24/0.8251 27.269/0.8311 - -
  • Pretrained models and SR results can be downloaded Here.
Owner
Long
Image/Video Restoration
Long
Corruption Invariant Learning for Re-identification

Corruption Invariant Learning for Re-identification The official repository for Benchmarks for Corruption Invariant Person Re-identification (NeurIPS

Minghui Chen 73 Dec 08, 2022
Direct Multi-view Multi-person 3D Human Pose Estimation

Implementation of NeurIPS-2021 paper: Direct Multi-view Multi-person 3D Human Pose Estimation [paper] [video-YouTube, video-Bilibili] [slides] This is

Sea AI Lab 251 Dec 30, 2022
Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022

LDL Paper | Supplementary Material Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution Jie Liang*, Hu

150 Dec 26, 2022
This repository contains a PyTorch implementation of "AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis".

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | Project Page | Paper | PyTorch implementation for the paper "AD-NeRF: Audio

551 Dec 29, 2022
Multi-query Video Retreival

Multi-query Video Retreival

Princeton Visual AI Lab 17 Nov 22, 2022
This is the code for the paper "Motion-Focused Contrastive Learning of Video Representations" (ICCV'21).

Motion-Focused Contrastive Learning of Video Representations Introduction This is the code for the paper "Motion-Focused Contrastive Learning of Video

11 Sep 23, 2022
A simple code to perform canny edge contrast detection on images.

CECED-Canny-Edge-Contrast-Enhanced-Detection A simple code to perform canny edge contrast detection on images. A simple code to process images using c

Happy N. Monday 3 Feb 15, 2022
[NeurIPS 2020] Official Implementation: "SMYRF: Efficient Attention using Asymmetric Clustering".

SMYRF: Efficient attention using asymmetric clustering Get started: Abstract We propose a novel type of balanced clustering algorithm to approximate a

Giannis Daras 46 Dec 22, 2022
Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.

Video Representation Learning by Recognizing Temporal Transformations [Project Page] Simon Jenni, Givi Meishvili, and Paolo Favaro. In ECCV, 2020. Thi

Simon Jenni 46 Nov 14, 2022
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval

CONQUER: Contexutal Query-aware Ranking for Video Corpus Moment Retreival PyTorch implementation of CONQUER: Contexutal Query-aware Ranking for Video

Hou zhijian 23 Dec 26, 2022
Grammar Induction using a Template Tree Approach

Gitta Gitta ("Grammar Induction using a Template Tree Approach") is a method for inducing context-free grammars. It performs particularly well on data

Thomas Winters 36 Nov 15, 2022
A library for researching neural networks compression and acceleration methods.

A library for researching neural networks compression and acceleration methods.

Intel Labs 100 Dec 29, 2022
CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.

CausalNLP CausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable. Install pip install -U

Arun S. Maiya 95 Jan 03, 2023
Implementation of FSGNN

FSGNN Implementation of FSGNN. For more details, please refer to our paper Experiments were conducted with following setup: Pytorch: 1.6.0 Python: 3.8

19 Dec 05, 2022
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)

PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar

Jang Hyun Cho 164 Dec 30, 2022
A fast MoE impl for PyTorch

An easy-to-use and efficient system to support the Mixture of Experts (MoE) model for PyTorch.

Rick Ho 873 Jan 09, 2023
Xview3 solution - XView3 challenge, 2nd place solution

Xview3, 2nd place solution https://iuu.xview.us/ test split aggregate score publ

Selim Seferbekov 24 Nov 23, 2022
This is a clean and robust Pytorch implementation of DQN and Double DQN.

DQN/DDQN-Pytorch This is a clean and robust Pytorch implementation of DQN and Double DQN. Here is the training curve: All the experiments are trained

XinJingHao 15 Dec 27, 2022
Ἀνατομή is a PyTorch library to analyze representation of neural networks

Ἀνατομή is a PyTorch library to analyze representation of neural networks

Ryuichiro Hataya 50 Dec 05, 2022
Blender Add-on that sets a Material's Base Color to one of Pantone's Colors of the Year

Blender PCOY (Pantone Color of the Year) MCMC (Mid-Century Modern Colors) HG71 (House & Garden Colors 1971) Blender Add-ons That Assign a Custom Color

Don Schnitzius 15 Nov 20, 2022