Gene Chou

I am a first year CS PhD student at Cornell University, advised by Noah Snavely and Bharath Hariharan. Previously, I received my bachelor's in computer science and math from Princeton University and worked with Felix Heide. My research focuses on 3D reconstruction and generation.


cv  /  github  /  linkedin  /  google scholar  /  pictures of my cat


YOLOR-Based Multi-Task Learning
Hung-Shuo Chang, Chien-Yao Wang, Richard Wang, Gene Chou, Hong-Yuan Mark Liao
Arxiv 2023

Builds on YOLOR to jointly train vision (e.g. object detection, instance and semantic segmentation) and vision-language (e.g. image captioning) tasks. Fast and lightweight while achieving competitive performance.

Thin On-Sensor Nanophotonic Array Cameras
Praneeth Chakravarthula, Jipeng Sun, Xiao Li, Chenyang Lei, Gene Chou, Mario Bijelic, Johannes Froesch, Arka Majumdar, Felix Heide

Recovers images in broadband using a single flat metasurface optic. Compensates for residual aberrations with probabilistic deconvolution implemented using a conditional diffusion model.

Diffusion-SDF: Conditional Generative Modeling of Signed Distance Functions
Gene Chou, Yuval Bahat, Felix Heide
ICCV 2023
paper / code / project page / teaser video

Performs diffusion on the latent space of neural SDFs while providing geometric guidance. Generates diverse meshes conditioned on partial point clouds, 2D images, and real-scanned, noisy point clouds.

GenSDF: Two-Stage Learning of Generalizable Signed Distance Functions
Gene Chou, Ilya Chugunov, Felix Heide
NeurIPS 2022
paper / code / project page

Combines a semi-supervised approach with a self-supervised loss to reconstruct neural SDFs from raw input point clouds of over a hundred unseen object classes.


Website template borrowed from Jon Barron.