This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation".

Related tags

Deep LearningObjProp
Overview

ObjProp

Introduction

This is the official implementation of the paper "Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation".

Installation

This repo is built using mmdetection. To install the dependencies, first clone the repository locally:

git clone https://github.com/anirudh-chakravarthy/objprop.git

Then, install PyTorch 1.1.0, torchvision 0.3.0, mmcv 0.2.12:

conda install pytorch==1.1.0 torchvision==0.3.0 -c pytorch
pip install mmcv==0.2.12

Then, install the CocoAPI for YouTube-VIS

conda install cython scipy
pip install git+https://github.com/youtubevos/cocoapi.git#"egg=pycocotools&subdirectory=PythonAPI"

Training

First, download and prepare the YouTube-VIS dataset using the following instructions.

To train ObjProp, run the following command:

python3 tools/train.py configs/masktrack_rcnn_r50_fpn_1x_youtubevos_objprop.py

In order to change the arguments such as dataset directory, learning rate, number of GPUs, etc, refer to the following configuration file configs/masktrack_rcnn_r50_fpn_1x_youtubevos_objprop.py.

Inference

To perform inference using ObjProp, run the following command:

python3 tools/test_video.py configs/masktrack_rcnn_r50_fpn_1x_youtubevos_objprop.py [MODEL_PATH] --out [OUTPUT_PATH.json] --eval segm

A JSON file with the inference results will be saved at OUTPUT_PATH.json. To evaluate the performance, submit the result file to the evaluation server.

License

ObjProp is released under the Apache 2.0 license.

Citation

@article{Chakravarthy2021ObjProp,
  author = {Anirudh S Chakravarthy and Won-Dong Jang and Zudi Lin and Donglai Wei and Song Bai and Hanspeter Pfister},  
  title = {Object Propagation via Inter-Frame Attentions for Temporally Stable Video Instance Segmentation},
  journal = {CoRR},
  volume = {abs/2111.07529},
  year = {2021},
  url = {https://arxiv.org/abs/2111.07529}
}
Owner
Anirudh S Chakravarthy
MS in Computer Vision, CMU | Research Intern, Harvard VCG | B.E. Computer Science, BITS Pilani. Visit my site for more.
Anirudh S Chakravarthy
A Broad Study on the Transferability of Visual Representations with Contrastive Learning

A Broad Study on the Transferability of Visual Representations with Contrastive Learning This repository contains code for the paper: A Broad Study on

Ashraful Islam 29 Nov 09, 2022
Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implicit Bayesian Inference"

GINC small-scale in-context learning dataset GINC (Generative In-Context learning Dataset) is a small-scale synthetic dataset for studying in-context

P-Lambda 29 Dec 19, 2022
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning

Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-Learning This is the official repository of "Camera Distortion-

Hanbyel Cho 12 Oct 06, 2022
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

Donny You 2.2k Jan 06, 2023
Garbage Detection system which will detect objects based on whether it is plastic waste or plastics or just garbage.

Garbage Detection using Yolov5 on Jetson Nano 2gb Developer Kit. Garbage detection system which will detect objects based on whether it is plastic was

Rishikesh A. Bondade 2 May 13, 2022
Simple PyTorch hierarchical models.

A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.

Rajiv Sarvepalli 5 Mar 06, 2022
PyTorch wrappers for using your model in audacity!

audacitorch This package contains utilities for prepping PyTorch audio models for use in Audacity. More specifically, it provides abstract classes for

Hugo Flores García 130 Dec 14, 2022
PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features

PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features Overview This repository is the Pytorch implementation of PRIN/SPRIN: On Extracting P

Yang You 17 Mar 02, 2022
Official project repository for 'Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination'

NCAE_UAD Official project repository of 'Normality-Calibrated Autoencoder for Unsupervised Anomaly Detection on Data Contamination' Abstract In this p

Jongmin Andrew Yu 2 Feb 10, 2022
本步态识别系统主要基于GaitSet模型进行实现

本步态识别系统主要基于GaitSet模型进行实现。在尝试部署本系统之前,建立理解GaitSet模型的网络结构、训练和推理方法。 系统的实现效果如视频所示: 演示视频 由于模型较大,部分模型文件存储在百度云盘。 链接提取码:33mb 具体部署过程 1.下载代码 2.安装requirements.txt

16 Oct 22, 2022
TDmatch is a Python library developed to perform matching tasks in three categories:

TDmatch TDmatch is a Python library developed to perform matching tasks in three categories: Text to Data which matches tuples of a table to text docu

Naser Ahmadi 5 Aug 11, 2022
Hyperparameter tuning for humans

KerasTuner KerasTuner is an easy-to-use, scalable hyperparameter optimization framework that solves the pain points of hyperparameter search. Easily c

Keras 2.6k Dec 27, 2022
Generate high quality pictures. GAN. Generative Adversarial Networks

ESRGAN generate high quality pictures. GAN. Generative Adversarial Networks """ Super-resolution of CelebA using Generative Adversarial Networks. The

Lieon 1 Dec 14, 2021
Course on computational design, non-linear optimization, and dynamics of soft systems at UIUC.

Computational Design and Dynamics of Soft Systems · This is a repository that contains the source code for generating the lecture notes, handouts, exe

Tejaswin Parthasarathy 4 Jul 21, 2022
Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving

Frequency Domain Image Translation: More Photo-realistic, Better Identity-preserving This is the source code for our paper Frequency Domain Image Tran

Mu Cai 52 Dec 23, 2022
Pytorch implementation of the paper: "A Unified Framework for Separating Superimposed Images", in CVPR 2020.

Deep Adversarial Decomposition PDF | Supp | 1min-DemoVideo Pytorch implementation of the paper: "Deep Adversarial Decomposition: A Unified Framework f

Zhengxia Zou 72 Dec 18, 2022
CausaLM: Causal Model Explanation Through Counterfactual Language Models

CausaLM: Causal Model Explanation Through Counterfactual Language Models Authors: Amir Feder, Nadav Oved, Uri Shalit, Roi Reichart Abstract: Understan

Amir Feder 39 Jul 10, 2022
Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF)

Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF

Lei Lin 21 Dec 18, 2022
Official implementation of the NeurIPS 2021 paper Online Learning Of Neural Computations From Sparse Temporal Feedback

Online Learning Of Neural Computations From Sparse Temporal Feedback This repository is the official implementation of the NeurIPS 2021 paper Online L

Lukas Braun 3 Dec 15, 2021
Pytorch implementation of "Neural Wireframe Renderer: Learning Wireframe to Image Translations"

Neural Wireframe Renderer: Learning Wireframe to Image Translations Pytorch implementation of ideas from the paper Neural Wireframe Renderer: Learning

Yuan Xue 7 Nov 14, 2022