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cs.CV2026

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…

cs.CV2024

InstantRestore: Single-Step Personalized Face Restoration with Shared-Image Attention

Howard Zhang, Yuval Alaluf, Sizhuo Ma +3

Face image restoration aims to enhance degraded facial images while addressing challenges such as diverse degradation types, real-time processing demands, and, most crucially, the…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2023

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…