Paper recorded by Signals 4 on 2026-08-28 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-08-28 on arXiv · recorded by Signals 4 on 2026-08-31
Category: cs.AI · 人工智能 · first seen 2026-08-31
Recent generative approaches to geometry estimation adapt pretrained image diffusion models and treat the task as image-conditioned generation. Leveraging off-the-shelf image diffusion models, they either (i) train task-specific geometry models (for depth and surface normal estimation) independently, losing the opportunity of exploring the intrinsic correlation of these geometric targets, or (ii)