Yuqun Wu

I am a second year PhD student in Computer Science department of University of Illinois at Urbana-Champaign, advised by Prof. Derek Hoiem. I also work closely with Prof. Shenlong Wang.

Prior to that, I also spent one year as a MS student and received my Bachelor of Science degree at UIUC, majoring in Computer Science & Statistics.

I did a summer intern at University of California San Diego in 2022, advised by Prof. Manmohan Chandraker

Email  /  CV  /  Linkedin

I am interested in Computer Vision. My interest mainly lies in 3D geometry, including single-view depth completion, indoor 3D representation, and inverse rendering.

Create 3D models that provide accurate geometry and view synthesis, partially closing the large geometric performance gap between NeRF and traditional MVS methods

Encode 3D scenes into extremely compact representation from 2D images and enable its transmittance, decoding and rendering in real-time across various platforms via traditional GL pipeline.

Investigate region based representation, combining class-agnostic segmentation from SAM and dense features from foundation models, for a wide variety of tasks, including semantic segmentation, object-based image retrieval, and multi-image analysis.

Propose a novel method that outperforms existing depth completion pipelines given sparse keypoint depth, and reconstructs complete point clouds given SfM setups

Present Quantized Fourier Features (QFF), which encodes features in bins of Fourier features, and can result in smaller model size, faster training, and better quality outputs for various applications of neural representation

Teaching Assistant: CS 445: Computational Photography (Fall 2022), CS 441: Applied Machine Learning (Spring 2023)

Reviewer: ECCV 2024, WACV 2025