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
This is the official repository of the paper Stocastic bandits with groups of similar arms (NeurIPS 2021). It contains the code that was used to compute the figures and experiments of the paper.

Experiments How to reproduce experimental results of Stochastic bandits with groups of similar arms submitted paper ? Section 5 of the paper To reprod

Fabien 0 Oct 25, 2021
The code of "Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer".

Code data_preprocess.py: preprocess data for Dependent-T5. parameters.py: define parameters of Dependent-T5. train_tools.py: traning and evaluation co

1 Apr 21, 2022
Flybirds - BDD-driven natural language automated testing framework, present by Trip Flight

Flybird | English Version 行为驱动开发(Behavior-driven development,缩写BDD),是一种软件过程的思想或者

Ctrip, Inc. 706 Dec 30, 2022
Official code for "End-to-End Optimization of Scene Layout" -- including VAE, Diff Render, SPADE for colorization (CVPR 2020 Oral)

End-to-End Optimization of Scene Layout Code release for: End-to-End Optimization of Scene Layout CVPR 2020 (Oral) Project site, Bibtex For help conta

Andrew Luo 41 Dec 09, 2022
A unified 3D Transformer Pipeline for visual synthesis

Overview This is the official repo for the paper: "NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion". NÜWA is a unified multimodal

Microsoft 2.6k Jan 03, 2023
Code release for ConvNeXt model

A ConvNet for the 2020s Official PyTorch implementation of ConvNeXt, from the following paper: A ConvNet for the 2020s. arXiv 2022. Zhuang Liu, Hanzi

Meta Research 4.6k Jan 08, 2023
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

CatBoost 6.9k Jan 04, 2023
TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning

TransZero++ This repository contains the testing code for the paper "TransZero++: Cross Attribute-guided Transformer for Zero-Shot Learning" submitted

Shiming Chen 6 Aug 16, 2022
A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

Segnet is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of http://arxiv.org/pdf/15

Pradyumna Reddy Chinthala 190 Dec 15, 2022
Code for NeurIPS 2020 article "Contrastive learning of global and local features for medical image segmentation with limited annotations"

Contrastive learning of global and local features for medical image segmentation with limited annotations The code is for the article "Contrastive lea

Krishna Chaitanya 152 Dec 22, 2022
DeepGNN is a framework for training machine learning models on large scale graph data.

DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in

Microsoft 45 Jan 01, 2023
This repo contains the code for paper Inverse Weighted Survival Games

Inverse-Weighted-Survival-Games This repo contains the code for paper Inverse Weighted Survival Games instructions general loss function (--lfn) can b

3 Jan 12, 2022
[NIPS 2021] UOTA: Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration.

UOTA: Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration This repository is the official PyTorch implementation of UOT

6 Jun 29, 2022
Demonstrational Session git repo for H SAF User Workshop (28/1)

5th H SAF User Workshop The 5th H SAF User Workshop supported by EUMeTrain will be held in online in January 24-28 2022. This repository contains inst

H SAF 4 Aug 04, 2022
A Real-World Benchmark for Reinforcement Learning based Recommender System

RL4RS: A Real-World Benchmark for Reinforcement Learning based Recommender System RL4RS is a real-world deep reinforcement learning recommender system

121 Dec 01, 2022
CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhancement

CBREN This is the Pytorch implementation for our IEEE TCSVT paper : CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhanceme

Zhao Hengrun 3 Nov 04, 2022
Based on the paper "Geometry-aware Instance-reweighted Adversarial Training" ICLR 2021 oral

Geometry-aware Instance-reweighted Adversarial Training This repository provides codes for Geometry-aware Instance-reweighted Adversarial Training (ht

Jingfeng 47 Dec 22, 2022
Final report with code for KAIST Course KSE 801.

Orthogonal collocation is a method for the numerical solution of partial differential equations

Chuanbo HUA 4 Apr 06, 2022
QICK: Quantum Instrumentation Control Kit

QICK: Quantum Instrumentation Control Kit The QICK is a kit of firmware and software to use the Xilinx RFSoC to control quantum systems. It consists o

81 Dec 15, 2022
A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains (IJCV submission)

wsss-analysis The code of: A Comprehensive Analysis of Weakly-Supervised Semantic Segmentation in Different Image Domains, arXiv pre-print 2019 paper.

Lyndon Chan 48 Dec 18, 2022