The official pytorch implemention of the CVPR paper "Temporal Modulation Network for Controllable Space-Time Video Super-Resolution".

Related tags

Deep LearningTMNet
Overview

This is the official PyTorch implementation of TMNet in the CVPR 2021 paper "Temporal Modulation Network for Controllable Space-Time VideoSuper-Resolution"[PDF]. Our TMNet can flexibly interpolate intermediate frames for space-time video super-resolution (STVSR).

Contents

  1. Requirements
  2. Installation
  3. Demo
  4. Training
  5. Testing
  6. Citations

Requirements

Installation

First, make sure your machine has a GPU, which is required for the DCNv2 module.

  1. Clone the TMNet repository.
git clone --recursive https://github.com/CS-GangXu/TMNet.git
  1. Compile the DCNv2:
cd $ROOT/codes/models/modules/DCNv2
bash make.sh
python test.py

Demo (To be uploaded at April 24, 2021 11:59PM (Pacific Time))

Training (To be uploaded at April 24, 2021 11:59PM (Pacific Time))

Testing (To be uploaded at April 24, 2021 11:59PM (Pacific Time))

Citations

If you find the code helpful in your research or work, please cite the following papers.

@InProceedings{xu2021temporal,
  author = {Gang Xu and Jun Xu and Zhen Li and Liang Wang and Xing Sun and Mingming Cheng},
  title = {Temporal Modulation Network for Controllable Space-Time VideoSuper-Resolution},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  month = {June},
  year = {2021}
}

@InProceedings{xiang2020zooming,
  author = {Xiang, Xiaoyu and Tian, Yapeng and Zhang, Yulun and Fu, Yun and Allebach, Jan P. and Xu, Chenliang},
  title = {Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  pages={3370--3379},
  month = {June},
  year = {2020}
}

@InProceedings{wang2019edvr,
  author    = {Wang, Xintao and Chan, Kelvin C.K. and Yu, Ke and Dong, Chao and Loy, Chen Change},
  title     = {EDVR: Video restoration with enhanced deformable convolutional networks},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},
  month     = {June},
  year      = {2019},
}

Acknowledgments

Our code is inspired by Zooming-Slow-Mo-CVPR-2020 and EDVR.

Contact

If you have any questions, feel free to E-mail Gang Xu with [email protected].

Owner
Gang Xu
Gang Xu
Official repository for the paper F, B, Alpha Matting

FBA Matting Official repository for the paper F, B, Alpha Matting. This paper and project is under heavy revision for peer reviewed publication, and s

Marco Forte 404 Jan 05, 2023
This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)

Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization This codebase is the official implementation of Test-Time Classifier A

47 Dec 28, 2022
Implementation for "Domain-Specific Bias Filtering for Single Labeled Domain Generalization"

DSBF Introduction This repository contains the implementation code for paper: Domain-Specific Bias Filtering for Single Labeled Domain Generalization

ScottYuan 7 Jan 05, 2023
Code release for The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification (TIP 2020)

The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification Code release for The Devil is in the Channels: Mutual-Channel

PRIS-CV: Computer Vision Group 230 Dec 31, 2022
Transfer Learning library for Deep Neural Networks.

Transfer and meta-learning in Python Each folder in this repository corresponds to a method or tool for transfer/meta-learning. xfer-ml is a standalon

Amazon 245 Dec 08, 2022
使用深度学习框架提取视频硬字幕;docker容器免安装深度学习库,使用本地api接口使得界面和后端识别分离;

extract-video-subtittle 使用深度学习框架提取视频硬字幕; 本地识别无需联网; CPU识别速度可观; 容器提供API接口; 运行环境 本项目运行环境非常好搭建,我做好了docker容器免安装各种深度学习包; 提供windows界面操作; 容器为CPU版本; 视频演示 https

歌者 16 Aug 06, 2022
An implementation of shampoo

shampoo.pytorch An implementation of shampoo, proposed in Shampoo : Preconditioned Stochastic Tensor Optimization by Vineet Gupta, Tomer Koren and Yor

Ryuichiro Hataya 69 Sep 10, 2022
Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021)

T2Net Task Transformer Network for Joint MRI Reconstruction and Super-Resolution (MICCAI 2021) [Paper][Code] Dependencies numpy==1.18.5 scikit_image==

64 Nov 23, 2022
Implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs".

PPO-BiHyb This is the official implementation of our NeurIPS 2021 paper "A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Grap

<a href=[email protected]"> 66 Nov 23, 2022
Official code for Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset

Official code for our Interspeech 2021 - Spoken ObjectNet: A Bias-Controlled Spoken Caption Dataset [1]*. Visually-grounded spoken language datasets c

Ian Palmer 3 Jan 26, 2022
The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

Knut(Ke) Chen 134 Jan 01, 2023
Dataset for the Research2Clinics @ NeurIPS 2021 Paper: What Do You See in this Patient? Behavioral Testing of Clinical NLP Models

Behavioral Testing of Clinical NLP Models This repository contains code for testing the behavior of clinical prediction models based on patient letter

Betty van Aken 2 Sep 20, 2022
Leaderboard, taxonomy, and curated list of few-shot object detection papers.

Leaderboard, taxonomy, and curated list of few-shot object detection papers.

Gabriel Huang 70 Jan 07, 2023
A big endian Gentoo port developed on a Pine64.org RockPro64

Gentoo-aarch64_be A big endian Gentoo port developed on a Pine64.org RockPro64 The endian wars are over... little endian won. As a result, it is incre

Rory Bolt 6 Dec 07, 2022
UniLM AI - Large-scale Self-supervised Pre-training across Tasks, Languages, and Modalities

Pre-trained (foundation) models across tasks (understanding, generation and translation), languages (100+ languages), and modalities (language, image, audio, vision + language, audio + language, etc.

Microsoft 7.6k Jan 01, 2023
Global-Local Attention for Emotion Recognition

Global-Local Attention for Emotion Recognition Requirements Python 3 Install tensorflow (or tensorflow-gpu) = 2.0.0 Install some other packages pip i

Minh Nhat Le 15 Apr 21, 2022
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics.

Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics. By Andres Milioto @ University of Bonn. (for the new P

Photogrammetry & Robotics Bonn 314 Dec 30, 2022
PyTorch implementation of the wavelet analysis from Torrence & Compo

Continuous Wavelet Transforms in PyTorch This is a PyTorch implementation for the wavelet analysis outlined in Torrence and Compo (BAMS, 1998). The co

Tom Runia 262 Dec 21, 2022
Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.

Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?

EPFL Machine Learning and Optimization Laboratory 9 Oct 25, 2022
Sample code and notebooks for Vertex AI, the end-to-end machine learning platform on Google Cloud

Google Cloud Vertex AI Samples Welcome to the Google Cloud Vertex AI sample repository. Overview The repository contains notebooks and community conte

Google Cloud Platform 560 Dec 31, 2022