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.

Contact: gene@cs.cornell.edu

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

Research


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

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
SIGGRAPH ASIA 2023
paper

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.

CV


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