• I am currently working as a Postdoctoral Researcher in the VISICS lab, which is part of ESAT-PSI at Katholieke Universiteit Leuven, under the mentorship of Prof. Tinne Tuytelaars. I obtained my Ph.D. degree from the VDI Center at the School of Information Science and Technology, ShanghaiTech University, where I was supervised by Prof. Jingyi Yu.

• I earned my Doctorate (Ph.D.) from the University of the Chinese Academy of Sciences, with ShanghaiTech University as my main training institution, in 2021. I received my Bachelor’s degree from Shanghai University in 2015.

• My research interests lie at the intersection of Neural Rendering and Computer Vision. My goal is to create easily accessible 3D content and bridge the gap in applying 3D technology to our daily lives.

Projects

V^3: Viewing Volumetric Videos on Mobiles via Streamable 2D Dynamic Gaussians

This work presents a novel approach that enables high-quality mobile rendering through the streaming of dynamic Gaussians.

SIGGRAPH Asia 2024 (TOG)

Navigating the Nuances: A Fine-grained Evaluation of Vision-Language Navigation

This study presents a novel evaluation framework for the Vision-Language Navigation (VLN) task. It aims to diagnose current models for various instruction categories at a finer-grained level.

EMNLP 2024 Findings

TeTriRF: Temporal Tri-Plane Radiance Fields for Efficient Free-Viewpoint Video

TeTriRF significantly reduces the storage size for Free-Viewpoint Video (FVV) while maintaining low-cost generation and rendering.

CVPR 2024

VideoRF: Rendering Dynamic Radiance Fields as 2D Feature Video Streams

VideoRF treats dynamic radiance fields as 2D feature streams, leveraging hardware video codecs and shaders for smooth, high-quality rendering on various devices.

CVPR 2024

NeVRF: Neural Video-based Radiance Fields for Long-duration Sequences

NeVRF marries neural radiance field with image-based rendering to support photo-realistic novel view synthesis on long-duration dynamic scenes.

3DV 2024

Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos

ReRF enables highly compressible and streamable radiance field modeling. Our ReRF-based codec scheme and streaming player gives users a rich interactive experience.

CVPR 2023

Multi-view Neural Human Rendering

NHR creates photorealistic free-viewpoint videos (FVV) using multi-view dynamic human captures, utilizing point-based neural rendering techniques.

CVPR 2020