The Official PyTorch Implementation of DiscoBox.

Related tags

Deep Learningweakly-supervised-learninginstance-segmentationsemantic-correspondence
Overview

NVIDIA Source Code License Python 3.8

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision

Paper | Project page | Demo (Youtube) | Demo (Bilibili)

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision.
Shiyi Lan, Zhiding Yu, Chris Choy, Subhashree Radhakrishnan, Guilin Liu, Yuke Zhu, Larry Davis, Anima Anandkumar
International Conference on Computer Vision (ICCV) 2021

This repository contains the official Pytorch implementation of training & evaluation code and pretrained models for DiscoBox. DiscoBox is a state of the art framework that can jointly predict high quality instance segmentation and semantic correspondence from box annotations.

We use MMDetection v2.10.0 as the codebase.

All of our models are trained and tested using automatic mixed precision, which leverages float16 for speedup and less GPU memory consumption.

Installation

This implementation is based on PyTorch==1.9.0, mmcv==2.13.0, and mmdetection==2.10.0

Please refer to get_started.md for installation.

Or you can download the docker image from our dockerhub repository.

Models

Results on COCO val 2017

Backbone Weights AP [email protected] [email protected] [email protected] [email protected] [email protected]
ResNet-50 download 30.7 52.6 30.6 13.3 34.1 45.6
ResNet-101-DCN download 35.3 59.1 35.4 16.9 39.2 53.0
ResNeXt-101-DCN download 37.3 60.4 39.1 17.8 41.1 55.4

Results on COCO test-dev

We also evaluate the models in the section Results on COCO val 2017 with the same weights on COCO test-dev.

Backbone Weights AP [email protected] [email protected] [email protected] [email protected] [email protected]
ResNet-50 download 32.0 53.6 32.6 11.7 33.7 48.4
ResNet-101-DCN download 35.8 59.8 36.4 16.9 38.7 52.1
ResNeXt-101-DCN download 37.9 61.4 40.0 18.0 41.1 53.9

Training

COCO

ResNet-50 (8 GPUs):

bash tools/dist_train.sh \
     configs/discobox/discobox_solov2_r50_fpn_3x.py 8

ResNet-101-DCN (8 GPUs):

bash tools/dist_train.sh \
     configs/discobox/discobox_solov2_r101_dcn_fpn_3x.py 8

ResNeXt-101-DCN (8 GPUs):

bash tools/dist_train.sh \
     configs/discobox/discobox_solov2_x101_dcn_fpn_3x.py 8

Pascal VOC 2012

ResNet-50 (4 GPUs):

bash tools/dist_train.sh \
     configs/discobox/discobox_solov2_voc_r50_fpn_6x.py 4

ResNet-101 (4 GPUs):

bash tools/dist_train.sh \
     configs/discobox/discobox_solov2_voc_r101_fpn_6x.py 4

Testing

COCO

ResNet-50 (8 GPUs):

bash tools/dist_test.sh \
     configs/discobox/discobox_solov2_r50_fpn_3x.py \
     work_dirs/coco_r50_fpn_3x.pth 8 --eval segm

ResNet-101-DCN (8 GPUs):

bash tools/dist_test.sh \
     configs/discobox/discobox_solov2_r101_dcn_fpn_3x.py \
     work_dirs/coco_r101_dcn_fpn_3x.pth 8 --eval segm

ResNeXt-101-DCN (GPUs):

bash tools/dist_test.sh \
     configs/discobox/discobox_solov2_x101_dcn_fpn_3x_fp16.py \
     work_dirs/coco_x101_dcn_fpn_3x.pth 8 --eval segm

Pascal VOC 2012 (COCO API)

ResNet-50 (4 GPUs):

bash tools/dist_test.sh \
     configs/discobox/discobox_solov2_voc_r50_fpn_3x_fp16.py \
     work_dirs/voc_r50_6x.pth 4 --eval segm

ResNet-101 (4 GPUs):

bash tools/dist_test.sh \
     configs/discobox/discobox_solov2_voc_r101_fpn_3x_fp16.py \
     work_dirs/voc_r101_6x.pth 4 --eval segm

Pascal VOC 2012 (Matlab)

Step 1: generate results

ResNet-50 (4 GPUs):

bash tools/dist_test.sh \
     configs/discobox/discobox_solov2_voc_r50_fpn_3x_fp16.py \
     work_dirs/voc_r50_6x.pth 4 \
     --format-only \
     --options "jsonfile_prefix=work_dirs/voc_r50_results.json"

ResNet-101 (4 GPUs):

bash tools/dist_test.sh \
     configs/discobox/discobox_solov2_voc_r101_fpn_3x_fp16.py \
     work_dirs/voc_r101_6x.pth 4 \
     --format-only \
     --options "jsonfile_prefix=work_dirs/voc_r101_results.json"

Step 2: format conversion

ResNet-50:

python tools/json2mat.pywork_dirs/voc_r50_results.json work_dirs/voc_r50_results.mat

ResNet-101:

python tools/json2mat.pywork_dirs/voc_r101_results.json work_dirs/voc_r101_results.mat

Step 3: evaluation

Please visit BBTP for the evaluation code written in Matlab.

PF-Pascal

Please visit this repository.

LICENSE

Please check the LICENSE file. DiscoBox may be used non-commercially, meaning for research or evaluation purposes only. For business inquiries, please contact [email protected].

Citation

@article{lan2021discobox,
  title={DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision},
  author={Lan, Shiyi and Yu, Zhiding and Choy, Christopher and Radhakrishnan, Subhashree and Liu, Guilin and Zhu, Yuke and Davis, Larry S and Anandkumar, Anima},
  journal={arXiv preprint arXiv:2105.06464},
  year={2021}
}
Owner
NVIDIA Research Projects
NVIDIA Research Projects
GitHub Repository https://arxiv.org/abs/2105.06464
An Official Repo of CVPR '20 "MSeg: A Composite Dataset for Multi-Domain Segmentation"

This is the code for the paper: MSeg: A Composite Dataset for Multi-domain Semantic Segmentation (CVPR 2020, Official Repo) [CVPR PDF] [Journal PDF] J

226 Nov 05, 2022
https://sites.google.com/cornell.edu/recsys2021tutorial

Counterfactual Learning and Evaluation for Recommender Systems (RecSys'21 Tutorial) Materials for "Counterfactual Learning and Evaluation for Recommen

yuta-saito 45 Nov 10, 2022
Fast EMD for Python: a wrapper for Pele and Werman's C++ implementation of the Earth Mover's Distance metric

PyEMD: Fast EMD for Python PyEMD is a Python wrapper for Ofir Pele and Michael Werman's implementation of the Earth Mover's Distance that allows it to

William Mayner 433 Dec 31, 2022
Context-Sensitive Misspelling Correction of Clinical Text via Conditional Independence, CHIL 2022

cim-misspelling Pytorch implementation of Context-Sensitive Spelling Correction of Clinical Text via Conditional Independence, CHIL 2022. This model (

Juyong Kim 11 Dec 19, 2022
[ACM MM2021] MGH: Metadata Guided Hypergraph Modeling for Unsupervised Person Re-identification

Introduction This project is developed based on FastReID, which is an ongoing ReID project. Projects BUC In projects/BUC, we implement AAAI 2019 paper

WuYiming 7 Apr 13, 2022
Implementation of Shape Generation and Completion Through Point-Voxel Diffusion

Shape Generation and Completion Through Point-Voxel Diffusion Project | Paper Implementation of Shape Generation and Completion Through Point-Voxel Di

Linqi Zhou 103 Dec 29, 2022
This repo contains the implementation of the algorithm proposed in Off-Belief Learning, ICML 2021.

Off-Belief Learning Introduction This repo contains the implementation of the algorithm proposed in Off-Belief Learning, ICML 2021. Environment Setup

Facebook Research 32 Jan 05, 2023
[CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation

[CVPR2021] Domain Consensus Clustering for Universal Domain Adaptation [Paper] Prerequisites To install requirements: pip install -r requirements.txt

Guangrui Li 84 Dec 26, 2022
Face Recognition & AI Based Smart Attendance Monitoring System.

In today’s generation, authentication is one of the biggest problems in our society. So, one of the most known techniques used for authentication is h

Sagar Saha 1 Jan 14, 2022
Exporter for Storage Area Network (SAN)

SAN Exporter Prometheus exporter for Storage Area Network (SAN). We all know that each SAN Storage vendor has their own glossary of terms, health/perf

vCloud 32 Dec 16, 2022
ONNX-GLPDepth - Python scripts for performing monocular depth estimation using the GLPDepth model in ONNX

ONNX-GLPDepth - Python scripts for performing monocular depth estimation using the GLPDepth model in ONNX

Ibai Gorordo 18 Nov 06, 2022
A simple consistency training framework for semi-supervised image semantic segmentation

PseudoSeg: Designing Pseudo Labels for Semantic Segmentation PseudoSeg is a simple consistency training framework for semi-supervised image semantic s

Google Interns 143 Dec 13, 2022
Monocular 3D pose estimation. OpenVINO. CPU inference or iGPU (OpenCL) inference.

human-pose-estimation-3d-python-cpp RealSenseD435 (RGB) 480x640 + CPU Corei9 45 FPS (Depth is not used) 1. Run 1-1. RealSenseD435 (RGB) 480x640 + CPU

Katsuya Hyodo 8 Oct 03, 2022
Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation

Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation [Arxiv] [Video] Evaluation code for Unrestricted Facial Geometry Reconstr

Matan Sela 242 Dec 30, 2022
Official implementation of "StyleCariGAN: Caricature Generation via StyleGAN Feature Map Modulation" (SIGGRAPH 2021)

StyleCariGAN in PyTorch Official implementation of StyleCariGAN:Caricature Generation via StyleGAN Feature Map Modulation in PyTorch Requirements PyTo

PeterZhouSZ 49 Oct 31, 2022
MoveNetを用いたPythonでの姿勢推定のデモ

MoveNet-Python-Example MoveNetのPythonでの動作サンプルです。 ONNXに変換したモデルも同梱しています。変換自体を試したい方はMoveNet_tf2onnx.ipynbを使用ください。 2021/08/24時点でTensorFlow Hubで提供されている以下モデ

KazuhitoTakahashi 38 Dec 17, 2022
Code for "MetaMorph: Learning Universal Controllers with Transformers", Gupta et al, ICLR 2022

MetaMorph: Learning Universal Controllers with Transformers This is the code for the paper MetaMorph: Learning Universal Controllers with Transformers

Agrim Gupta 50 Jan 03, 2023
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation

Manas Bommakanti 1 Jan 22, 2022
Implementation of the ICCV'21 paper Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases

Temporally-Coherent Surface Reconstruction via Metric-Consistent Atlases [Papers 1, 2][Project page] [Video] The implementation of the papers Temporal

56 Nov 21, 2022
QAHOI: Query-Based Anchors for Human-Object Interaction Detection (paper)

QAHOI QAHOI: Query-Based Anchors for Human-Object Interaction Detection (paper) Requirements PyTorch = 1.5.1 torchvision = 0.6.1 pip install -r requ

38 Dec 29, 2022