7 papers
Evidential Neural Radiance Fields
Ruxiao Duan, Alex Wong
Understanding sources of uncertainty is fundamental to trustworthy three-dimensional scene modeling. While recent advances in neural radiance fields (NeRFs) achieve impressive accu…
WorldBench: Benchmarking Physical Understanding of World Models by Isolating Physics Concepts
Rishi Upadhyay, Howard Zhang, Jim Solomon +5
Recent advances in generative foundational models, often termed "world models," have propelled interest in applying them to critical tasks like robotic planning and autonomous syst…
All-day Depth Completion
Vadim Ezhov, Hyoungseob Park, Zhaoyang Zhang +7
We propose a method for depth estimation under different illumination conditions, i.e., day and night time. As photometry is uninformative in regions under low-illumination, we tac…
GT-Rain Single Image Deraining Challenge Report
Howard Zhang, Yunhao Ba, Ethan Yang +20
This report reviews the results of the GT-Rain challenge on single image deraining at the UG2+ workshop at CVPR 2023. The aim of this competition is to study the rainy weather phen…
WeatherProof: Leveraging Language Guidance for Semantic Segmentation in Adverse Weather
Blake Gella, Howard Zhang, Rishi Upadhyay +7
We propose a method to infer semantic segmentation maps from images captured under adverse weather conditions. We begin by examining existing models on images degraded by weather c…
WeatherProof: A Paired-Dataset Approach to Semantic Segmentation in Adverse Weather
Blake Gella, Howard Zhang, Rishi Upadhyay +5
The introduction of large, foundational models to computer vision has led to drastically improved performance on the task of semantic segmentation. However, these existing methods…
Enhancing Diffusion Models with 3D Perspective Geometry Constraints
Rishi Upadhyay, Howard Zhang, Yunhao Ba +5
While perspective is a well-studied topic in art, it is generally taken for granted in images. However, for the recent wave of high-quality image synthesis methods such as latent d…