Ting-Hsuan Chen

I am currently a master's student in Computer Science at the University of Southern California, advised by Professor Yue Wang.

I have previously worked as an R&D engineer at Foxconn and also served as a research assistant in Professor Yu-Lun Liu's laboratory at National Yang Ming Chiao Tung University.

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News

Sep, 2024 My paper has been accepted by NeurIPS 2024🥳
Aug, 2024 Begin my Master's degree at USC in Fall 2024.

Research

I'm interested in computer vision, deep learning, generative AI, 3D reconstruction, video editing, and image processing.

MoonSim: A Photorealistic Lunar Environment Simulator
Ting-Hsuan Chen*, Henghui Bao*, Ziyu Chen*, Haozhe Lou, Ge Yang, Zhiwen Fan, Marco Pavone, Yue Wang,
CVPR, 2025 (under review)
project page

MoonSim is a photo-realistic lunar scene simulator that incorporates Unreal Engine for high-quality lunar images with realistic lighting and shadows and MuJoCo for physics simulation, supporting diverse locomotion and navigation tasks.

NaRCan: Natural Refined Canonical Image with Integration of Diffusion Prior for Video Editing
Ting-Hsuan Chen, Jiewen Chan, Hau-Shiang Shiu, Shih Han Yen, Changhan Yeh, Yu-Lun Liu,
NeurIPS, 2024
project page / arXiv / code / demo

NaRCan, a video editing framework, integrates a hybrid deformation field network with diffusion priors to address the challenge of maintaining the canonical image as a natural image.

DiffIR2VR-Zero: Zero-Shot Video Restoration with Diffusion-based Image Restoration Models
Changhan Yeh, Chin-Yang Lin, Zhixiang Wang, Chi-Wei Hsiao, Ting-Hsuan Chen, Yu-Lun Liu,
ICLR, 2025 (under review)
project page / arXiv / code / demo

This paper introduces a novel zero-shot video restoration method using pre-trained image restoration diffusion models, achieving excellent performance across diverse datasets and extreme video degradations.

Project

GPU-SplineTransformer
Ting-Hsuan Chen
github, 2022

My GPU-Optimized SplineTransformer significantly accelerates the conversion of large data arrays into B-spline bases by leveraging GPU power. This innovation outperforms traditional CPU-based solutions, offering enhanced speed and efficiency for your data processing needs.