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首次观测 · 记录 #1CVF · CVPR 2026:cvf:125cdbab12ccfd4f71ca1d0ddc956e47CVF · CVPR 2026

SeeGroup: Multi-Layer Depth Estimation of Transparent Surfaces via Self-Determined Grouping

Wen, Hongyu, Deng, Jia

原文摘要

Transparent objects are common in daily life, and understanding their multi-layer depth information, including both the transparent surface and the objects behind it, is crucial for real-world applications that interact with transparent materials.However, existing depth methods produce only a single depth map, which is inherently ambiguous for transparent surfaces.In this work, We propose a multi-layer depth estimation method, SeeGroup, consisting of novel recurrent decomposition module design and an intensity-based formulation for multi-layer depth. Experiments demonstrate that our method significantly improves the state of the art of multi-layer depth estimation, improving quadruplet relative depth accuracy on LayeredDepth benchmark from 61.34% to 70.09%.

cs.CV

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition · 2026 · 正式发表