Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image (ICCV 2021)

Overview

Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image

Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image

Baowen Zhang, Yangang Wang, Xiaoming Deng*, Yinda Zhang*, Ping Tan, Cuixia Ma and Hongan Wang

Project page       Paper       Supp

prediction example

This repository contains the model of the ICCV'2021 paper "Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image".

We propose a novel deep learning framework to reconstruct 3D hand poses and shapes of two interacting hands from a single color image. Previous methods designed for single hand cannot be easily applied for the two hand scenario because of the heavy inter-hand occlusion and larger solution space. In order to address the occlusion and similar appearance between hands that may confuse the network, we design a hand pose-aware attention module to extract features associated to each individual hand respectively. We then leverage the two hand context presented in interaction and propose a context-aware cascaded refinement that improves the hand pose and shape accuracy of each hand conditioned on the context between interacting hands. Extensive experiments on the main benchmark datasets demonstrate that our method predicts accurate 3D hand pose and shape from single color image, and achieves the state-of-the-art performance.

1.Installation

This code is tested with Cuda 11.1.

Clone this repository.

git clone https://github.com/BaowenZ/Two-Hand-Shape-Pose.git
cd Two-Hand-Shape-Pose

In the following, ${TWO_HAND} refers to Two-Hand-Shape-Pose.

Install dependencies

conda create -n intershape python=3.9
conda activate intershape
pip install --upgrade pip
pip install -r requirements.txt -f https://download.pytorch.org/whl/torch_stable.html

2.Download models

Download pre-trained model model.pts and put it into folder model/.

Download the MANO model files from MANO. Unzip mano_v1_2.zip under ${TWO_HAND} and rename the unzipped folder as mano/.

3.Running the code

python test.py --test_folder test_data --model_path model/model.pts

Our model predicts hand meshes from images in test_data/. The estimated meshes are saved as obj files in test_data/.

Citation

Please consider citing the paper if you use this code.

@inproceedings{Zhang2021twohand, 
      title={Interacting Two-Hand 3D Pose and Shape Reconstruction from Single Color Image}, 
      author={Baowen Zhang, Yangang Wang, Xiaoming Deng, Yinda Zhang, Ping Tan, Cuixia Ma and Hongan Wang}, 
      booktitle={International Conference on Computer Vision (ICCV)}, 
      year={2021} 
} 

4. Acknowledgement

We use part of the great code from InterNet and mano layer.

Image samples in test_data/ are from InterHand2.6M.

We thank the authors of InterNet, InterHand2.6M and mano layer for their great work.

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs

SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs SMORE is a a versatile framework that scales multi-hop query emb

Google Research 135 Dec 27, 2022
FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack

FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack Case study of the FCA. The code can be find in FCA. Cas

IDRL 21 Dec 15, 2022
Benchmarking the robustness of Spatial-Temporal Models

Benchmarking the robustness of Spatial-Temporal Models This repositery contains the code for the paper Benchmarking the Robustness of Spatial-Temporal

Yi Chenyu Ian 15 Dec 16, 2022
A sample pytorch Implementation of ACL 2021 research paper "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".

Span-ASTE-Pytorch This repository is a pytorch version that implements Ali's ACL 2021 research paper Learning Span-Level Interactions for Aspect Senti

来自丹麦的天籁 10 Dec 06, 2022
Catalyst.Detection

Accelerated DL R&D PyTorch framework for Deep Learning research and development. It was developed with a focus on reproducibility, fast experimentatio

Catalyst-Team 12 Oct 25, 2021
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale

EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud

19 Sep 20, 2022
PyTorch implementation of "PatchGame: Learning to Signal Mid-level Patches in Referential Games" to appear in NeurIPS 2021

PatchGame: Learning to Signal Mid-level Patches in Referential Games This repository is the official implementation of the paper - "PatchGame: Learnin

Kamal Gupta 22 Mar 16, 2022
Out-of-Town Recommendation with Travel Intention Modeling (AAAI2021)

TrainOR_AAAI21 This is the official implementation of our AAAI'21 paper: Haoran Xin, Xinjiang Lu, Tong Xu, Hao Liu, Jingjing Gu, Dejing Dou, Hui Xiong

Jack Xin 13 Oct 19, 2022
This is the 3D Implementation of 《Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation》

CoraNet This is the 3D Implementation of 《Inconsistency-aware Uncertainty Estimation for Semi-supervised Medical Image Segmentation》 Environment pytor

25 Nov 08, 2022
Efficient neural networks for analog audio effect modeling

micro-TCN Efficient neural networks for audio effect modeling

Christian Steinmetz 94 Dec 29, 2022
Contains a bunch of different python programm tasks

py_tasks Contains a bunch of different python programm tasks Armstrong.py - calculate Armsrong numbers in range from 0 to n with / without cache and c

Dmitry Chmerenko 1 Dec 17, 2021
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression

Patch-Based Deep Autoencoder for Point Cloud Geometry Compression Overview The ever-increasing 3D application makes the point cloud compression unprec

17 Dec 05, 2022
A deep-learning pipeline for segmentation of ambiguous microscopic images.

Welcome to Official repository of deepflash2 - a deep-learning pipeline for segmentation of ambiguous microscopic images. Quick Start in 30 seconds se

Matthias Griebel 39 Dec 19, 2022
Simple ONNX operation generator. Simple Operation Generator for ONNX.

sog4onnx Simple ONNX operation generator. Simple Operation Generator for ONNX. https://github.com/PINTO0309/simple-onnx-processing-tools Key concept V

Katsuya Hyodo 6 May 15, 2022
UDP++ (ECCVW 2020 Oral), (Winner of COCO 2020 Keypoint Challenge).

UDP-Pose This is the pytorch implementation for UDP++, which won the Fisrt place in COCO Keypoint Challenge at ECCV 2020 Workshop. Top-Down Results on

20 Jul 29, 2022
Research on controller area network Intrusion Detection Systems

Group members information Member 1: Lixue Liang Member 2: Yuet Lee Chan Member 3: Xinruo Zhang Member 4: Yifei Han User Manual Generate Attack Packets

Roche 4 Aug 30, 2022
SCU OlympicsRunning Baseline

Competition 1v1 running Environment check details in Jidi Competition RLChina2021智能体竞赛 做出的修改: 奖励重塑:修改了环境,重新设置了奖励的分配,使得奖励组成不只有零和博弈,还有探索环境的奖励。 算法微调:修改了官

ZiSeoi Wong 2 Nov 23, 2021
A collection of metrics for evaluating timbre dissimilarity using the TorchMetrics API

Timbre Dissimilarity Metrics A collection of metrics for evaluating timbre dissimilarity using the TorchMetrics API Installation pip install -e . Usag

Ben Hayes 21 Jan 05, 2022
Back to the Feature: Learning Robust Camera Localization from Pixels to Pose (CVPR 2021)

Back to the Feature with PixLoc We introduce PixLoc, a neural network for end-to-end learning of camera localization from an image and a 3D model via

Computer Vision and Geometry Lab 610 Jan 05, 2023
links and status of cool gradio demos

awesome-demos This is a list of some wonderful demos & applications built with Gradio. Here's how to contribute yours! 🖊️ Natural language processing

Gradio 96 Dec 30, 2022