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oneThousand1000 committed Apr 17, 2024
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4 changes: 2 additions & 2 deletions _pages/about.md
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- /about.html
---

![bar](https://raw.githubusercontent.com/oneThousand1000/oneThousand1000.github.io/master/images/bar.png)
<img src="https://raw.githubusercontent.com/oneThousand1000/oneThousand1000.github.io/master/images/bar.png" alt="bar" style="zoom: 80%;" />

I am Yiqian Wu (吴奕谦), a CS Ph.D. student (since 2021) at the [State Key Lab of CAD&CG](http://www.cad.zju.edu.cn), Zhejiang University, under the supervision of Prof. [Xiaogang Jin](http://www.cad.zju.edu.cn/home/jin). Prior to this, I accomplished my Bachelor's degree in Computer Science and Technology, graduating with honors from the Chu Kochen College at Zhejiang University in 2021.

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## 2024 ![1f431](http://oneThousand1000.github.io/images/1f431.png)
1. [Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior](https://onethousandwu.com/publication/Portrait3D)

Preprint
ACM Transactions on Graphics (Proceedings of SIGGRAPH 2024)

**Yiqian Wu**, Hao Xu, Xiangjun Tang, Xien Chen, Siyu Tang, Zhebin Zhang, Chen Li, Xiaogang Jin*

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Education
======
# Education and Experience

## Academic guest at ETH Zurich

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# Publications



## 2024
1. [Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior](https://onethousandwu.com/publication/Portrait3D)

Preprint

**Yiqian Wu**, Hao Xu, Xiangjun Tang, Xien Chen, Siyu Tang, Zhebin Zhang, Chen Li, Xiaogang Jin*



## 2023

1. [3DPortraitGAN: Learning One-Quarter Headshot 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses](https://onethousandwu.com/publication/3DPortraitGAN)

Preprint

**Yiqian Wu**, Hao Xu, Xiangjun Tang, Hongbo Fu, Xiaogang Jin

2. [LPFF: A Portrait Dataset for Face Generators Across Large Poses](https://onethousandwu.com/publication/lpff-dataset)

2023 IEEE/CVF International Conference on Computer Vision (ICCV)

**Yiqian Wu**, Jing Zhang, Hongbo Fu, Xiaogang Jin.

4. [Deep Real-time Volumetric Rendering Using Multi-feature Fusion](https://onethousandwu.com/publication/mrpnn)

ACM SIGGRAPH 2023 Conference Proceedings (SIGGRAPH '23). Association for Computing Machinery, New York, NY, USA, Article 61, 1–10.

Jinkai Hu, Chengzhong Yu, Hongli Liu, Ling-qi Yan, **Yiqian Wu**, Xiaogang Jin.



## 2022

1. [HairMapper: Removing Hair from Portraits Using GANs](https://onethousandwu.com/publication/hair_mapper_cvpr2022)

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

**Yiqian Wu**, Yongliang Yang, Xiaogang Jin.



## 2021

1. [Coarse-to-Fine: Facial Structure Editing of Portrait Images via Latent Space Classifications](https://onethousandwu.com/publication/coarse-to-fine)

ACM Trans. Graph. 40, 4, Article 46 (August 2021), 13 pages.

**Yiqian Wu**, Yongliang Yang, Qinjie Xiao, Xiaogang Jin.

2. [EyelashNet: A Dataset and A Baseline Method for Eyelash Matting](https://onethousandwu.com/publication/eyelashnet)

ACM Trans. Graph. 40, 6, Article 217 (December 2021), 17 pages.

Qinjie Xiao, Hanyuan Zhang, Zhaorui Zhang, **Yiqian Wu**, Luyuan Wang, Xiaogang Jin, Xinwei Jiang, Yongliang Yang, Tianjia Shao, Kun Zhou.



## 2020

1. [iOrthoPredictor: Model-guided Deep Prediction of Teeth Alignment](https://onethousandwu.com/publication/iothopredictor)

ACM Transactions on Graphics (Proc. of Siggraph Asia 2020), 39(6), Article 216., 2020

Lingchen Yang, Zefeng Shi, **Yiqian Wu**, Xiang Li, Kun Zhou, Hongbo Fu, Youyi Zheng.



# Awards and Honors

- 2021-2022 Zhejiang University-Suzhou Talent Scholarship
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6 changes: 6 additions & 0 deletions _publications/3DPortraitGAN.md
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---
![coarse2fine](http://oneThousand1000.github.io/images/publications/3DPortraitGAN.png)

> **[Preprint] 3DPortraitGAN: Learning One-Quarter Headshot 3D GANs from a Single-View Portrait Dataset with Diverse Body Poses**
>
> [Yiqian Wu](https://onethousandwu.com/), [Hao Xu](https://xh38.github.io/), [Xiangjun Tang](https://yuyujunjun.github.io/), [Hongbo Fu](http://sweb.cityu.edu.hk/hongbofu/publications.html), [Xiaogang Jin*](http://www.cad.zju.edu.cn/home/jin)


<b>Abstract:</b>

3D-aware face generators are typically trained on 2D real-life face image datasets that primarily consist of near-frontal face data, and as such, they are unable to construct [one-quarter headshot](https://www.backstage.com/magazine/article/types-of-headshots-75557/) 3D portraits with complete head, neck, and shoulder geometry. Two reasons account for this issue: First, existing facial recognition methods struggle with extracting facial data captured from large camera angles or back views. Second, it is challenging to learn a distribution of 3D portraits covering the one-quarter headshot region from single-view data due to significant geometric deformation caused by diverse body poses. To this end, we first create the dataset 360°-Portrait-HQ (360°PHQ for short) which consists of high-quality single-view real portraits annotated with a variety of camera parameters (the yaw angles span the entire 360° range) and body poses. We then propose 3DPortraitGAN, the first 3D-aware one-quarter headshot portrait generator that learns a canonical 3D avatar distribution from the 360°PHQ dataset with body pose self-learning. Our model can generate view-consistent portrait images from all camera angles with a canonical one-quarter headshot 3D representation. Our experiments show that the proposed framework can accurately predict portrait body poses and generate view-consistent, realistic portrait images with complete geometry from all camera angles.
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permalink: /publication/Portrait3D
excerpt: '**Yiqian Wu**, [Hao Xu](https://xh38.github.io/), [Xiangjun Tang](https://yuyujunjun.github.io/), [Xien Chen](https://github.com/xienchenn), [Siyu Tang](https://inf.ethz.ch/people/person-detail.MjYyNzgw.TGlzdC8zMDQsLTg3NDc3NjI0MQ==.html), Zhebin Zhang, Chen Li, [Xiaogang Jin*](http://www.cad.zju.edu.cn/home/jin)'
date: 2024-03-24
venue: "preprint"
venue: "ACM Transactions on Graphics (Proceedings of SIGGRAPH 2024)"
paperurl: 'https://arxiv.org/abs/2404.10394'
citation: 'http://oneThousand1000.github.io/files/bibtex/portrait3d.html'
citation: 'http://onethousand1000.github.io/files/bibtex/portrait3d.html'
code: 'https://github.com/oneThousand1000/Portrait3D'
video: 'https://youtu.be/z7xWiD1p1_4'
supplementary_materials: 'https://drive.google.com/file/d/1LasG-urCA7rEoITHofBwEk0CloXM0DwX/view?usp=sharing'
project_page: 'https://onethousandwu.com/Portrait3D.github.io/'
year: '2024'
first_author: 'yes'
teaser: 'http://oneThousand1000.github.io/images/publications/portrait3d.png'
teaser: 'http://oneThousand1000.github.io/images/publications/portrait3D.png'
---
![portrait3d](http://oneThousand1000.github.io/images/publications/portrait3d.png)



> **Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior**
>
> ACM Transactions on Graphics (Proceedings of SIGGRAPH 2024)
>
> [Yiqian Wu](https://onethousandwu.com/), [Hao Xu](https://xh38.github.io/), [Xiangjun Tang](https://yuyujunjun.github.io/), [Xien Chen](https://vision.cs.yale.edu/members/xien-chen.html), [Siyu Tang](https://inf.ethz.ch/people/person-detail.MjYyNzgw.TGlzdC8zMDQsLTg3NDc3NjI0MQ==.html), Zhebin Zhang, Chen Li, [Xiaogang Jin*](http://www.cad.zju.edu.cn/home/jin)


<b>Abstract:</b>

Existing neural rendering-based text-to-3D-portrait generation methods typically make use of human geometry prior and diffusion models to obtain guidance. However, relying solely on geometry information introduces issues such as the Janus problem, over-saturation, and over-smoothing.
We present Portrait3D, a novel neural rendering-based framework with a novel joint geometry-appearance prior to achieve text-to-3D-portrait generation that overcomes the aforementioned issues. To accomplish this, we train a 3D portrait generator, 3DPortraitGAN-Pyramid, as a robust prior. This generator is capable of producing 360° canonical 3D portraits, serving as a starting point for the subsequent diffusion-based generation process. To mitigate the "grid-like" artifact caused by the high-frequency information in the feature-map-based 3D representation commonly used by most 3D-aware GANs, we integrate a novel pyramid tri-grid 3D representation into 3DPortraitGAN-Pyramid. To generate 3D portraits from text, we first project a randomly generated image aligned with the given prompt into the pre-trained 3DPortraitGAN-Pyramid's latent space. The resulting latent code is then used to synthesize a pyramid tri-grid. Beginning with the obtained pyramid tri-grid, we use score distillation sampling to distill the diffusion model's knowledge into the pyramid tri-grid. Following that, we utilize the diffusion model to refine the rendered images of the 3D portrait and then use these refined images as training data to further optimize the pyramid tri-grid, effectively eliminating issues with unrealistic color and unnatural artifacts.
Our experimental results show that Portrait3D can produce realistic, high-quality, and canonical 3D portraits that align with the prompt.

[![Project](https://img.shields.io/badge/Portrait3D-1?label=Project&color=8B93FF&logo=data:image/svg+xml;charset=utf-8;base64,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)](https://onethousandwu.com/Portrait3D.github.io/)
[![Paper](https://img.shields.io/badge/Main%20Paper-1?color=58A399&logo=data:image/svg+xml;charset=utf-8;base64,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)](https://arxiv.org/abs/2404.10394)
[![Suppl](https://img.shields.io/badge/Supplementary-1?color=378CE7&logo=data:image/svg+xml;charset=utf-8;base64,PHN2ZyB0PSIxNzEyNDkwMTgyMzc1IiBjbGFzcz0iaWNvbiIgdmlld0JveD0iMCAwIDEwMjQgMTAyNCIgdmVyc2lvbj0iMS4xIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHAtaWQ9Ijg5MDIiIHdpZHRoPSIyMDAiIGhlaWdodD0iMjAwIj48cGF0aCBkPSJNNDg2LjQgNDA5LjZIMjgyLjE4NTE0M2E0MS4zOTg4NTcgNDEuMzk4ODU3IDAgMCAwLTQxLjc2NDU3MiA0MC45NmMwIDIyLjY3NDI4NiAxOC43MjQ1NzEgNDAuOTYgNDEuNzY0NTcyIDQwLjk2aDk2LjMyOTE0M2EzNjIuNzg4NTcxIDM2Mi43ODg1NzEgMCAwIDAtOTYuMzI5MTQzIDI0NS43NmMwIDk0LjU3MzcxNCAzNi42NDQ1NzEgMTgwLjUxNjU3MSA5Ni4zMjkxNDMgMjQ1Ljc2SDE1Ni43NDUxNDNBODIuNzk3NzE0IDgyLjc5NzcxNCAwIDAgMSA3My4xNDI4NTcgOTAxLjEyVjgxLjkyQzczLjE0Mjg1NyAzNi42NDQ1NzEgMTEwLjU5MiAwIDE1Ni43NDUxNDMgMGg2NjguNzQ1MTQzYzQ2LjA4IDAgODMuNjAyMjg2IDM2LjY0NDU3MSA4My42MDIyODUgODEuOTJ2MzgxLjE0NzQyOWEzODAuMTk2NTcxIDM4MC4xOTY1NzEgMCAwIDAtNDIyLjYxOTQyOC01My4zOTQyODZ6IG0yNTUuNDg4LTE2My44NGMwLTIyLjY3NDI4Ni0xOC43MjQ1NzEtNDAuOTYtNDEuODM3NzE0LTQwLjk2SDI4Mi4xMTJhNDEuMzk4ODU3IDQxLjM5ODg1NyAwIDAgMC00MS43NjQ1NzEgNDAuOTZjMCAyMi42NzQyODYgMTguNzI0NTcxIDQwLjk2IDQxLjc2NDU3MSA0MC45Nmg0MTcuOTM4Mjg2YzIzLjExMzE0MyAwIDQxLjgzNzcxNC0xOC4yODU3MTQgNDEuODM3NzE0LTQwLjk2ek02NTguMjg1NzE0IDQ1MC41NmMxNjEuNjQ1NzE0IDAgMjkyLjU3MTQyOSAxMjguMzY1NzE0IDI5Mi41NzE0MjkgMjg2LjcyUzgxOS45MzE0MjkgMTAyNCA2NTguMjg1NzE0IDEwMjRzLTI5Mi41NzE0MjktMTI4LjM2NTcxNC0yOTIuNTcxNDI4LTI4Ni43MiAxMzAuOTI1NzE0LTI4Ni43MiAyOTIuNTcxNDI4LTI4Ni43MnogbS0xMjUuMzY2ODU3IDMyNy42OGg4My42MDIyODZ2ODEuOTJjMCAyMi42NzQyODYgMTguNjUxNDI5IDQwLjk2IDQxLjc2NDU3MSA0MC45NiAyMy4xMTMxNDMgMCA0MS43NjQ1NzEtMTguMjg1NzE0IDQxLjc2NDU3Mi00MC45NnYtODEuOTJoODMuNjAyMjg1YzIzLjExMzE0MyAwIDQxLjgzNzcxNC0xOC4yODU3MTQgNDEuODM3NzE1LTQwLjk2IDAtMjIuNjc0Mjg2LTE4LjcyNDU3MS00MC45Ni00MS44Mzc3MTUtNDAuOTZINzAwLjA1MDI4NlY2MTQuNGMwLTIyLjY3NDI4Ni0xOC42NTE0MjktNDAuOTYtNDEuNzY0NTcyLTQwLjk2YTQxLjM5ODg1NyA0MS4zOTg4NTcgMCAwIDAtNDEuNzY0NTcxIDQwLjk2djgxLjkySDUzMi45MTg4NTdhNDEuMzk4ODU3IDQxLjM5ODg1NyAwIDAgMC00MS44Mzc3MTQgNDAuOTZjMCAyMi42NzQyODYgMTguNzI0NTcxIDQwLjk2IDQxLjgzNzcxNCA0MC45NnoiIGZpbGw9IiNmZmZmZmYiIHAtaWQ9Ijg5MDMiPjwvcGF0aD48L3N2Zz4=)](https://drive.google.com/file/d/1LasG-urCA7rEoITHofBwEk0CloXM0DwX/view?usp=sharing)
[![Video](https://img.shields.io/badge/Video-1?color=E178C5&logo=data:image/svg+xml;charset=utf-8;base64,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)](https://youtu.be/z7xWiD1p1_4)
[![Github](https://img.shields.io/github/stars/oneThousand1000/Portrait3D)](https://github.com/oneThousand1000/Portrait3D)
[![dataset-on-hf](https://huggingface.co/datasets/huggingface/badges/raw/main/dataset-on-hf-sm.svg)](https://huggingface.co/datasets/onethousand/Portrait3D_gallery)




Recommended citation:
```
@misc{wu2024portrait3d,
title={Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior},
author={Yiqian Wu and Hao Xu and Xiangjun Tang and Xien Chen and Siyu Tang and Zhebin Zhang and Chen Li and Xiaogang Jin},
year={2024},
eprint={2404.10394},
archivePrefix={arXiv},
primaryClass={cs.CV}
@article{Portrait3D_sig24,
author = {Wu, Yiqian and Xu, Hao and Tang, Xiangjun and Chen, Xien and Tang, Siyun and Zhang, Zhebin and Li, Chen and Jin, Xiaogang},
title = {Portrait3D: Text-Guided High-Quality 3D Portrait Generation Using Pyramid Representation and GANs Prior},
year = {2024},
publisher = {Association for Computing Machinery},
volume = {43},
number = {4},
url = {https://doi.org/10.1145/3658162},
doi = {10.1145/3658162},
journal = {ACM Trans. Graph.},
month = {Jul}
}
```
10 changes: 10 additions & 0 deletions _publications/coarse-to-fine.md
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Expand Up @@ -17,6 +17,16 @@ teaser: 'http://oneThousand1000.github.io/images/publications/coarse2fine.png'
---
![coarse2fine](http://oneThousand1000.github.io/images/publications/coarse2fine.png)



> **Coarse-to-Fine: Facial Structure Editing of Portrait Images via Latent Space Classifications**
>
> ACM Transactions on Graphics (Proceedings of SIGGRAPH 2021)
>
> [Yiqian Wu](https://onethousandwu.com/), [Yongliang Yang](https://www.yongliangyang.net/), Qinjie Xiao, [Xiaogang Jin*](http://www.cad.zju.edu.cn/home/jin/).


<b>Abstract:</b>

Facial structure editing of portrait images is challenging given the facial variety, the lack of ground-truth, the necessity of jointly adjusting color and shape, and the requirement of no visual artifacts. In this paper, we investigate how to perform chin editing as a case study of editing facial structures. We present a novel method that can automatically remove the double chin effect in portrait images. Our core idea is to train a fine classification boundary in the latent space of the portrait images. This can be used to edit the chin appearance by manipulating the latent code of the input portrait image while preserving the original portrait features. To achieve such a fine separation boundary, we employ a carefully designed training stage based on latent codes of paired synthetic images with and without a double chin. In the testing stage, our method can automatically handle portrait images with only a refinement to subtle misalignment before and after double chin editing. Our model enables alteration to the neck region of the input portrait image while keeping other regions unchanged, and guarantees the rationality of neck structure and the consistency of facial characteristics. To the best of our knowledge, this presents the first effort towards an effective application for editing double chins. We validate the efficacy and efficiency of our approach through extensive experiments and user studies.
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