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Official Torch7 implementation of "V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map", CVPR 2018
| Date | Stars |
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| 2026-07-24 | 391 |
| 2026-07-25 | 391 |
| 2026-07-28 | 391 |
| 2026-07-30 | 391 |
| 2026-08-06 | 391 |
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[](https://paperswithcode.com/sota/hand-pose-estimation-on-hands-2017?p=v2v-posenet-voxel-to-voxel-prediction-network)
[](https://paperswithcode.com/sota/hand-pose-estimation-on-icvl-hands?p=v2v-posenet-voxel-to-voxel-prediction-network)
[](https://paperswithcode.com/sota/pose-estimation-on-itop-front-view?p=v2v-posenet-voxel-to-voxel-prediction-network)
[](https://paperswithcode.com/sota/pose-estimation-on-itop-top-view?p=v2v-posenet-voxel-to-voxel-prediction-network)
[](https://paperswithcode.com/sota/hand-pose-estimation-on-nyu-hands?p=v2v-posenet-voxel-to-voxel-prediction-network)
[](https://paperswithcode.com/sota/hand-pose-estimation-on-msra-hands?p=v2v-posenet-voxel-to-voxel-prediction-network)
# V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map
**PyTorch re-implementation of the V2V-PoseNet is available at dragonbook's [repo](https://github.com/dragonbook/V2V-PoseNet-pytorch).**
Thanks dragonbook for re-implementation. Other versions of the V2V-PoseNet are also welcome!
# Introduction
This is our project repository for the paper, **V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map ([CVPR 2018](http://cvpr2018.thecvf.com))**.
We, **Team SNU CVLAB**, (<i>Gyeongsik Moon, Juyong Chang</i>, and <i>Kyoung Mu Lee</i> of [**Computer Vision Lab, Seoul National University**](https://cv.snu.ac.kr/)) are **winners** of [**HANDS2017 Challenge**](http://icvl.ee.ic.ac.uk/hands17/challenge/) on frame-based 3D hand pose estimation.
Please refer to our paper for details.
If you find our work useful in your research or publication, please cite our work:
[1] Moon, Gyeongsik, Ju Yong Chang, and Kyoung Mu Lee. **"V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map."** <i>CVPR 2018. </i> [[arXiv](https://arxiv.org/abs/1711.07399)]
```
@InProceedings{Moon_2018_CVPR_V2V-PoseNet,
author = {Moon, Gyeongsik and Chang, Juyong and Lee, Kyoung Mu},
title = {V2V-PoseNet: Voxel-to-Voxel Prediction Network for Accurate 3D Hand and Human Pose Estimation from a Single Depth Map},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2018}
}
```
In this repository, we provide
* Our model architecture description (V2V-PoseNet)
* HANDS2017 frame-based 3D hand pose estimation Challenge Results
* Comparison with the previous state-of-the-art methods
* Training code
* Datasets we used (ICVL, NYU, MSRA, ITOP)
* Trained models and estimated results
* 3D hand and human pose estimation examples
## Model Architecture
## HANDS2017 frame-based 3D hand pose estimation Challenge Results
## Comparison with the previous state-of-the-art methods
![PapExcerpt of 8,225 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:96f26a995f7c02f5, topic:computer-vision, readme:computer vision, desc:pose estimation
matched fp:96f26a995f7c02f5, topic:deep-learning