Lowest memory consumption and second shortest runtime in NTIRE 2022 challenge on Efficient Super-Resolution

Last update: Dec 01, 2022

Overview

FMEN

Lowest memory consumption and second shortest runtime in NTIRE 2022 on Efficient Super-Resolution.

Our paper: Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution .

Main Contribution

Enhanced Residual Block.
High-Frequency Attention Block.
Batch Normalization layers can be applied to attention branch to boost performance.

Train

Our goal is to design a strightforward but powerful backbone for lightweight image super-resolution, so the testing model topology is really simple (only contains five highly optimized operators: 3x3 convolution, LeakyReLU, element-wise addition, element-wise multiplication and sigmoid).

Since there are no other tricks, you can directly adopt EDSR framework to train the model.

Owner

GitHub Repository

RL and distillation in CARLA using a factorized world model

World on Rails Learning to drive from a world on rails Dian Chen, Vladlen Koltun, Philipp Krähenbühl, arXiv techical report (arXiv 2105.00636) This re

131 Dec 16, 2022

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

LSTMs for Human Activity Recognition Human Activity Recognition (HAR) using smartphones dataset and an LSTM RNN. Classifying the type of movement amon

3.1k Dec 30, 2022

Code for the paper "Asymptotics of ℓ2 Regularized Network Embeddings"

README Code for the paper Asymptotics of L2 Regularized Network Embeddings. Requirements Requires Stellargraph 1.2.1, Tensorflow 2.6.0, scikit-learm 0

0 Jan 06, 2022

This is the code for CVPR 2021 oral paper: Jigsaw Clustering for Unsupervised Visual Representation Learning

JigsawClustering Jigsaw Clustering for Unsupervised Visual Representation Learning Pengguang Chen, Shu Liu, Jiaya Jia Introduction This project provid

73 Sep 18, 2022

A PyTorch implementation of Mugs proposed by our paper "Mugs: A Multi-Granular Self-Supervised Learning Framework".

Mugs: A Multi-Granular Self-Supervised Learning Framework This is a PyTorch implementation of Mugs proposed by our paper "Mugs: A Multi-Granular Self-

62 Nov 08, 2022

Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other

ML_Model_implementaion Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other dectree_model: Implementation o

3 Jan 24, 2022

Cards Against Humanity AI

cah-ai This is a Cards Against Humanity AI implemented using a pre-trained Semantic Search model. How it works A player is described by a combination

2 Aug 22, 2022

TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments for IV 2022.

TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi

42 Dec 09, 2022

Implementations for the ICLR-2021 paper: SEED: Self-supervised Distillation For Visual Representation.

27 Oct 23, 2022

TorchOk - The toolkit for fast Deep Learning experiments in Computer Vision

52 Dec 23, 2022

Official Implementation for Fast Training of Neural Lumigraph Representations using Meta Learning.

Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst

39 Oct 08, 2022

Object recognition using Azure Custom Vision AI and Azure Functions

Step by Step on how to create an object recognition model using Custom Vision, export the model and run the model in an Azure Function

11 Jul 08, 2022

Code for EMNLP 2021 paper: "Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training"

SCAPT-ABSA Code for EMNLP2021 paper: "Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training" Overvie

66 Dec 04, 2022

generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search

generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search This repository contains single-threaded TreeMesh code. I'm Hua Tong, a senior stu

18 Sep 21, 2022

Unofficial implementation of Proxy Anchor Loss for Deep Metric Learning

Proxy Anchor Loss for Deep Metric Learning Unofficial pytorch, tensorflow and mxnet implementations of Proxy Anchor Loss for Deep Metric Learning. Not

3 Jun 09, 2021

Network Compression via Central Filter

Network Compression via Central Filter Environments The code has been tested in the following environments: Python 3.8 PyTorch 1.8.1 cuda 10.2 torchsu

2 May 12, 2022

Drone detection using YOLOv5

This drone detection system uses YOLOv5 which is a family of object detection architectures and we have trained the model on Drone Dataset. Overview I

27 Dec 20, 2022

In the AI for TSP competition we try to solve optimization problems using machine learning.

AI for TSP Competition Goal In the AI for TSP competition we try to solve optimization problems using machine learning. The competition will be hosted

11 Nov 27, 2022

CoSMA: Convolutional Semi-Regular Mesh Autoencoder. From Paper "Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes"

Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes Implementation of CoSMA: Convolutional Semi-Regular Mesh Autoencoder arXiv p

10 Oct 11, 2022

This repo provides function call to track multi-objects in videos

Custom Object Tracking Introduction This repo provides function call to track multi-objects in videos with a given trained object detection model and

51 Nov 22, 2022