Update README

README.md

@@ -1,12 +1,60 @@
-# Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning
+<div align="center">
 
-## Data Preparation
+<h1>HaMuCo: Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning</h1>
+
+<div>
+    <a href='https://scholar.google.com/citations?user=3hSD41oAAAAJ' target='_blank'>Xiaozheng Zheng<sup>1,2†</sup></a>&emsp;
+    <a href='https://scholar.google.com/citations?user=v8TFZI4AAAAJ' target='_blank'>Chao Wen<sup>2†</sup></a>&emsp;
+    <a href='https://scholar.google.com/citations?&user=ECKq3aUAAAAJ' target='_blank'>Zhou Xue<sup>2</sup></a>&emsp;
+    <a href='https://pengfeiren96.github.io/' target='_blank'>Pengfei Ren<sup>1,2</sup></a>&emsp;
+    <a href='https://jericwang.github.io/' target='_blank'>Jingyu Wang<sup>1*</sup></a>
+</div>
+<div>
+    <sup>1</sup>Beijing University of Posts and Telecommunications &emsp; <sup>2</sup>PICO IDL ByteDance &emsp; 
+</div>
+<div>
+    <sup>†</sup>Equal contribution &emsp; <sup>*</sup>Corresponding author
+</div>
+<div>
+    :star_struck: <strong>Accepted to ICCV 2023</strong>
+</div>
+
+---
+
+<img src="assets/HaMuCo-teaser-2.png" width="100%"/>
+
+<strong> HaMuCo is a multi-view self-supervised 3D hand pose estimation method that only requires 2D pseudo labels for training.</strong>
+
+---
+
+<h4 align="center">
+  <a href="https://zxz267.github.io/HaMuCo/" target='_blank'>[Project Page]</a> •
+  <a href="https://arxiv.org/abs/2302.00988" target='_blank'>[arXiv]</a>
+</h4>
+
+</div>
+
+## :black_square_button: TODO
+
+- [ ] FreiHAND evaluation code
+
+- [ ] Multi-view inference code
+
+## :mega: Updates
+
+[07/2023] HaMuCo is accepted to ICCV 2023:partying_face:!
+
+[01/2023] Training and evaluation codes on HanCo are released.
+
+
+
+## :desktop_computer: Data Preparation
 ### 1. Download the [HanCo](https://lmb.informatik.uni-freiburg.de/resources/datasets/HanCo.en.html) dataset from the official website.
-  1. https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_rgb.zip
-  2. https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_xyz.zip
-  3. https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_shape.zip
-  4. https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_calib_meta.zip
-  5. https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_rgb_merged.zip
+  - https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_rgb.zip
+  - https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_xyz.zip
+  - https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_shape.zip
+  - https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_calib_meta.zip
+  - https://lmb.informatik.uni-freiburg.de/data/HanCo/HanCo_rgb_merged.zip
 ### 2. We provide the 2D pseudo labels generated from OpenPose in `./data/HanCo/HaMuCo_*.zip`.
 ### 3. Unzip files and organize the data as follows:
 ```
@@ -19,7 +67,9 @@ ${ROOT}
 |   |   |-- rgb_merged
 |   |   |-- xyz
 ```
-## Installation
+
+
+## :desktop_computer: Installation
 ### Requirements
 - Python=3.7
 - PyTorch=1.9.1+cu111
@@ -33,5 +83,24 @@ cd HaMuCo
 pip install -r ./requirements.txt
 ```
 
-## Training
-### 1. Run `./train.py` to train and evaluate on the HanCo dataset.
+## :running_woman: Training
+### 1. Run `./train.py` to train and evaluate on the HanCo dataset.
+
+## :love_you_gesture: Citation
+If you find our work useful for your research, please consider citing the paper:
+```
+@inproceedings{
+  zheng2023hamuco,
+  title={HaMuCo: Hand Pose Estimation via Multiview Collaborative Self-Supervised Learning},
+  author={Zheng, Xiaozheng and Wen, Chao and Xue, Zhou and Ren, Pengfei and Wang, Jingyu},
+  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
+  year={2023}
+}
+```
+
+## :newspaper_roll: License
+
+Distributed under the MIT License. See `LICENSE` for more information.
+
+## :raised_hands: Acknowledgements
+The pytorch implementation of MANO is based on manopth. We thank the authors for their great job!