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Latent Bridge: From Video Latents to 3D Geometry via Feature Alignment

Paper recorded by Signals 4 on 2026-10-20 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-20 on arXiv · recorded by Signals 4 on 2026-10-21

Category: cs.CV · 计算机视觉 · first seen 2026-10-21

Abstract

Video generation and feed-forward 3D reconstruction typically use separate representations, requiring RGB decoding and visual re-encoding to recover geometry from generated latents. We propose Latent Bridge, which connects video generative latent spaces with geometric feature spaces to directly predict 3D geometry from video latents. We develop representation-specific bridges for Wan2.1 and V-RAE,

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#217 most recent of 756 cs.CV papers we have recorded · ↑ newer: VLM-Guided Contact Retargeting and Generative Partner Modeling for Hum · ↓ older: VideoMaMa++: Temporally Consistent Video Matting via Preserve-and-Refi
Cite this page: Latent Bridge: From Video Latents to 3D Geometry via Feature Alignment: the #217 most recent of 756 cs.CV papers we have recorded (as of 2026-10-20). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/latent-bridge-from-video-latents-to-3d-geometry-via-feature-alignment.html
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