Chaoyi Zhou

I am a PhD student in Computer Science at Clemson University advised by Prof. Siyu Huang. Previously, I obtanined my M.S. in Computer Science from University of Southern California, where I worked advised by Prof. Yajie Zhao . I received my B.E. in Computer Science and Technology from Nanjing University of Posts and Telecommunications in 2020.

My research interets including computer vision and generative model. Currently, I am focusing on 3D vision with implict representation and 3D content generation.

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News

2025.03: I will join Microsoft as a Research Intern!

2025.01: One paper is accepted to ICLR.

2024.09: One paper is accepted to NeurIPS as Spotlight (3.5% of 15671 submissions).

2024.01: I will join Vision and Learning Lab in Clemson University as a PhD student!

Selected Publications

* indicates equal contribution

Bézier Splatting for Fast and Differentiable Vector Graphics
Xi Liu, Chaoyi Zhou, Nanxuan Zhao, Siyu Huang
arxiv preprint, 2025  
project page / arXiv

This work introduces a new differentiable VG representation, dubbed Bézier splatting, that enables fast yet high-fidelity VG rasterization. Bézier splatting samples 2D Gaussians along Bézier curves, which naturally provide positional gradients at object boundaries.

Latent Radiance Fields with 3D-aware 2D Representations
Chaoyi Zhou*, Xi Liu*, Feng Luo, Siyu Huang
ICLR, 2025  
project page / arXiv / code

In this work, we propose a method to achieve 3D-aware 2D representations and enable 3D reconstruction in the latent space. Our LRF enables 3D reconstruction on the 2D latent space instead of the image space. It can render high-quality and photorealistic novel views, even for the unbounded scenes.

3DGS-Enhancer: Enhancing Unbounded 3D Gaussian Splatting with View-consistent 2D Diffusion Priors
Xi Liu*, Chaoyi Zhou*, Siyu Huang
NeurIPS, 2024   (Spotlight)
project page / arXiv / code

3DGS-Enhancer restores view-consistent latent features of rendered novel views and integrates them with the input views through a spatial-temporal decoder. The enhanced views are then used to fine-tune the initial 3DGS model, significantly improving its rendering performance.

Service

Conference Reviewer: ICCV 2025, ICML 2025, ICLR 2025, NeurIPS 2024.


Design and source code from Jon Barron's website