Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Related tags

Deep LearningHMMN
Overview

Hierarchical Memory Matching Network for Video Object Segmentation

Hongje Seong, Seoung Wug Oh, Joon-Young Lee, Seongwon Lee, Suhyeon Lee, Euntai Kim

ICCV 2021

no_image

This is the implementation of HMMN.
This code is based on STM (ICCV 2019): [link].
Please see our paper for the details: [paper]

Hierarchical Memory Matching Network for Video Object Segmentation (ICCV 2021)

Dependencies

  • Python 3.8
  • PyTorch 1.8.1
  • numpy, opencv, pillow

Trained model

  • Download pre-trained weights into the same folder with demo scripts
    Link: [weights]

Code

  • DAVIS-2016 validation set (Single-object)
python eval_DAVIS.py -g '0' -s val -y 16 -D [path/to/DAVIS]
  • DAVIS-2017 validation set (Multi-object)
python eval_DAVIS.py -g '0' -s val -y 17 -D [path/to/DAVIS]

Pre-computed Results

We also provide pre-computed results for benchmark sets.

Bibtex

@inproceedings{seong2021hierarchical,
  title={Hierarchical Memory Matching Network for Video Object Segmentation},
  author={Seong, Hongje and Oh, Seoung Wug and Lee, Joon-Young and Lee, Seongwon and Lee, Suhyeon and Kim, Euntai},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  year={2021}
}

Terms of Use

This software is for non-commercial use only. The source code is released under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) Licence (see this for details)

Owner
Hongje Seong
Hongje Seong
Tutel MoE: An Optimized Mixture-of-Experts Implementation

Project Tutel Tutel MoE: An Optimized Mixture-of-Experts Implementation. Supported Framework: Pytorch Supported GPUs: CUDA(fp32 + fp16), ROCm(fp32) Ho

Microsoft 344 Dec 29, 2022
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

TorchMultimodal (Alpha Release) Introduction TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.

Meta Research 663 Jan 06, 2023
Official Tensorflow implementation of "M-LSD: Towards Light-weight and Real-time Line Segment Detection"

M-LSD: Towards Light-weight and Real-time Line Segment Detection Official Tensorflow implementation of "M-LSD: Towards Light-weight and Real-time Line

NAVER/LINE Vision 357 Jan 04, 2023
Decorators for maximizing memory utilization with PyTorch & CUDA

torch-max-mem This package provides decorators for memory utilization maximization with PyTorch and CUDA by starting with a maximum parameter size and

Max Berrendorf 10 May 02, 2022
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.

counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code

Networks Learning 11 Dec 09, 2022
PyTorch implementation of Towards Accurate Alignment in Real-time 3D Hand-Mesh Reconstruction (ICCV 2021).

Towards Accurate Alignment in Real-time 3D Hand-Mesh Reconstruction Introduction This is official PyTorch implementation of Towards Accurate Alignment

TANG Xiao 96 Dec 27, 2022
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

Aitor Ruano 87 Dec 16, 2022
Caffe: a fast open framework for deep learning.

Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR)/The Berke

Berkeley Vision and Learning Center 33k Dec 28, 2022
This repository contains all source code, pre-trained models related to the paper "An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator"

An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o

Cuong Nguyen 3 Nov 15, 2021
Implementation for our ICCV2021 paper: Internal Video Inpainting by Implicit Long-range Propagation

Implicit Internal Video Inpainting Implementation for our ICCV2021 paper: Internal Video Inpainting by Implicit Long-range Propagation paper | project

202 Dec 30, 2022
Predictive Maintenance LSTM

Predictive-Maintenance-LSTM - Predictive maintenance study for Complex case study, we've obtained failure causes by operational error and more deeply by design mistakes.

Amir M. Sadafi 1 Dec 31, 2021
Imposter-detector-2022 - HackED 2022 Team 3IQ - 2022 Imposter Detector

HackED 2022 Team 3IQ - 2022 Imposter Detector By Aneeljyot Alagh, Curtis Kan, Jo

Joshua Ji 3 Aug 20, 2022
Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch

Semantic Segmentation Easy to use and customizable SOTA Semantic Segmentation models with abundant datasets in PyTorch Features Applicable to followin

sithu3 530 Jan 05, 2023
Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)

scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A

郭飞 3.7k Jan 03, 2023
Hand Gesture Volume Control | Open CV | Computer Vision

Gesture Volume Control Hand Gesture Volume Control | Open CV | Computer Vision Use gesture control to change the volume of a computer. First we look i

Jhenil Parihar 3 Jun 15, 2022
TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A good teacher is patient and consistent by Beyer et al.

FunMatch-Distillation TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A g

Sayak Paul 67 Dec 20, 2022
A Transformer-Based Siamese Network for Change Detection

ChangeFormer: A Transformer-Based Siamese Network for Change Detection (Under review at IGARSS-2022) Wele Gedara Chaminda Bandara, Vishal M. Patel Her

Wele Gedara Chaminda Bandara 214 Dec 29, 2022
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

Alexander Amini 75 Dec 15, 2022
Object classification with basic computer vision techniques

naive-image-classification Object classification with basic computer vision techniques. Final assignment for the computer vision course I took at univ

2 Jul 01, 2022
Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

Feng 2 Nov 19, 2021