Event-ID: Intrinsic Decomposition Using an Event Camera

摘要

Reconstructing 3D scenes from multi-view images is challenging, especially under extreme scenarios. We propose Event-ID, an event-based intrinsic decomposition framework that leverages events and images for stable decomposition under extreme scenarios. Our method is based on two observations: event cameras maintain good imaging quality under blurry or poorly exposed scenarios, and event signals from different viewpoints exhibit similarity in diffuse regions while varying in specular regions. We establish an event-based reflectance model and introduce an event-based warping method to extract specular clues. Our two-stage framework constructs a radiance field and decomposes the scene into normal, material, and lighting. Experimental results demonstrate superior performance compared to state-of-the-art methods. Our project can be found at https://zehaoc.github.io/EventID.github.io/