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
The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"

SIGIR2021-EGLN The implement of paper "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization" Neural graph based Col

15 Dec 27, 2022
HyDiff: Hybrid Differential Software Analysis

HyDiff: Hybrid Differential Software Analysis This repository provides the tool and the evaluation subjects for the paper HyDiff: Hybrid Differential

Yannic Noller 22 Oct 20, 2022
PyTorch implementation of "Dataset Knowledge Transfer for Class-Incremental Learning Without Memory" (WACV2022)

Dataset Knowledge Transfer for Class-Incremental Learning Without Memory [Paper] [Slides] Summary Introduction Installation Reproducing results Citati

Habib Slim 5 Dec 05, 2022
Tensorflow Implementation of ECCV'18 paper: Multimodal Human Motion Synthesis

MT-VAE for Multimodal Human Motion Synthesis This is the code for ECCV 2018 paper MT-VAE: Learning Motion Transformations to Generate Multimodal Human

Xinchen Yan 36 Oct 02, 2022
A comprehensive list of published machine learning applications to cosmology

ml-in-cosmology This github attempts to maintain a comprehensive list of published machine learning applications to cosmology, organized by subject ma

George Stein 290 Dec 29, 2022
A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning

CLEVR Dataset Generation This is the code used to generate the CLEVR dataset as described in the paper: CLEVR: A Diagnostic Dataset for Compositional

Facebook Research 503 Jan 04, 2023
Unsupervised Learning of Video Representations using LSTMs

Unsupervised Learning of Video Representations using LSTMs Code for paper Unsupervised Learning of Video Representations using LSTMs by Nitish Srivast

Elman Mansimov 341 Dec 20, 2022
Learning from graph data using Keras

Steps to run = Download the cora dataset from this link : https://linqs.soe.ucsc.edu/data unzip the files in the folder input/cora cd code python eda

Mansar Youness 64 Nov 16, 2022
Quickly and easily create / train a custom DeepDream model

Dream-Creator This project aims to simplify the process of creating a custom DeepDream model by using pretrained GoogleNet models and custom image dat

55 Dec 27, 2022
Wider-Yolo Kütüphanesi ile Yüz Tespit Uygulamanı Yap

WIDER-YOLO : Yüz Tespit Uygulaması Yap Wider-Yolo Kütüphanesinin Kullanımı 1. Wider Face Veri Setini İndir Train Dataset Val Dataset Test Dataset Not:

Kadir Nar 6 Aug 22, 2022
End-To-End Crowdsourcing

End-To-End Crowdsourcing Comparison of traditional crowdsourcing approaches to a state-of-the-art end-to-end crowdsourcing approach LTNet on sentiment

Andreas Koch 1 Mar 06, 2022
Yolo ros - YOLO-ROS for HUAWEI ATLAS200

YOLO-ROS YOLO-ROS for NVIDIA YOLO-ROS for HUAWEI ATLAS200, please checkout for b

ChrisLiu 5 Oct 18, 2022
StarGAN v2 - Official PyTorch Implementation (CVPR 2020)

StarGAN v2 - Official PyTorch Implementation StarGAN v2: Diverse Image Synthesis for Multiple Domains Yunjey Choi*, Youngjung Uh*, Jaejun Yoo*, Jung-W

Clova AI Research 3.1k Jan 09, 2023
This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize over continuous domains by Brandon Amos

Tutorial on Amortized Optimization This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize

Meta Research 144 Dec 26, 2022
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage

Microsoft 5.7k Jan 09, 2023
List of awesome things around semantic segmentation 🎉

Awesome Semantic Segmentation List of awesome things around semantic segmentation 🎉 Semantic segmentation is a computer vision task in which we label

Dam Minh Tien 18 Nov 26, 2022
Apache Spark - A unified analytics engine for large-scale data processing

Apache Spark Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an op

The Apache Software Foundation 34.7k Jan 04, 2023
PPO Lagrangian in JAX

PPO Lagrangian in JAX This repository implements PPO in JAX. Implementation is tested on the safety-gym benchmark. Usage Install dependencies using th

Karush Suri 2 Sep 14, 2022
Official code of paper "PGT: A Progressive Method for Training Models on Long Videos" on CVPR2021

PGT Code for paper PGT: A Progressive Method for Training Models on Long Videos. Install Run pip install -r requirements.txt. Run python setup.py buil

Bo Pang 27 Mar 30, 2022
Chinese clinical named entity recognition using pre-trained BERT model

Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi

Xiangyang Li 109 Dec 14, 2022