Yangyi Huang

Yangyi Huang (黄洋逸)

I am an incoming PhD student at the Chinese University of Hong Kong, supervised by Weiyang Liu, as well as a research assistant at Yandong Wen's lab, Westlake University.

I interned at NVIDIA Research, collaborating with Ye Yuan and Umar Iqbal on digital human generation and reconstruction. Earlier, I worked with Hongwei Yi, Yuliang Xiu, and Justus Thies on related research in 3D human modeling and synthesis.

In 2024, I received my Master's degree at State Key Lab of CAD&CG, College of Computer Science and Technology at Zhejiang University under the supervision by Prof. Deng Cai. Before that, I received my B.Eng(2017.09 - 2021.06) in Computer Science from the same department.

Email / CV / Google Scholar / X / Github

News

08/2023 We released TeCH and TADA! on arXiv!
07/2023 Our paper ELICIT is accepted to ICCV 2023!
07/2023 Invited to give a talk on Full-body avatars from single images and textual guidance at Perceiving Systems, MPI-IS

Research

My research interest lies in computer vision, neural rendering and generative modeling. Currently I mainly focus on creating 3D contents and modelling 3D humans. Representative papers/projects are highlighted.

	GAvatar: Animatable 3D Gaussian Avatars with Implicit Mesh Learning Ye Yuan, Xueting Li, Yangyi Huang, Shalini De Mello, Koki Nagano, Jan Kautz, Umar Iqbal (* denotes equal contribution) CVPR, 2024 (Highlight) arXiv / project / video We seek to leverage Gaussian splatting to generate realistic animatable avatars from textual descriptions, addressing the limitations (e.g., flexibility and efficiency) imposed by mesh or NeRF-based representations.
	TeCH: Text-guided Reconstruction of Lifelike Clothed Humans Yangyi Huang, Hongwei Yi, Yuliang Xiu, Tingting Liao, Jiaxiang Tang, Deng Cai, Justus Thies ( denotes equal contribution) 3DV, 2024 code / arXiv / project / video We reconstruct high-resolution textured meshes for clothed humans from single images, with textual guidance from a VQA model and a few-shot finetuned T2I model.
	TADA! Text to Animatable Digital Avatars Tingting Liao, Hongwei Yi, Yuliang Xiu, Jiaxiang Tang, Yangyi Huang, Justus Thies, Michael J. Black 3DV, 2024 code / arXiv / project / video We create expressive 3D avatars from text, based on T2I (I: image; T: text) model.
	One-shot Implicit Animatable Avatars with Model-based Priors Yangyi Huang, Hongwei Yi, Weiyang Liu, Haofan Wang, Boxi Wu, Wenxiao Wang, Binbin Lin, Debing Zhang, Deng Cai(* denotes equal contribution) ICCV, 2023 code / arXiv / project We create a animatable NeRF-based avatar reconstruction from a single image with model-based prior.
	BEVFormer++: Improving BEVFormer for 3D Camera-only Object Detection Zhiqi Li, Hanming Deng, Tianyu Li, Yangyi Huang, Chonghao Sima, Xiangwei Geng, Yulu Gao, Wenhai Wang, Yang Li, Lewei Lu 1st place solution for Waymo Open Dataset Challenge 2022 report We enhanced BEVFormer, a DETR-based 3D detection model, with efficient techniques.
	FuseFormer: Fusing Fine-Grained Information in Transformers for Video Inpainting Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu Wenxiu Sun, Xiaogang Wang, Jifeng Dai, Hongsheng Li ( denotes equal contribution) ICCV, 2021 code / arXiv We proposed a Transformer-based model to inpaint videos with sharp and realistic results.

Service

Reviewer for CVPR, ICCV, TVCG and SIGGRAPH.

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