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Learning to Correct Geometry in Generated Videos

Paper recorded by Signals 4 on 2026-10-16 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.CV · 计算机视觉 · first seen 2026-10-19

Abstract

Generated videos often lose geometric consistency under camera motion: structures warp under viewpoint change, parallax becomes inconsistent, and smooth camera movement may collapse into shot-like transitions. We argue that this failure is largely a data problem. In web-scale video corpora, most visible motion comes from dynamic objects captured by static or weakly moving cameras, leaving only spa

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#231 most recent of 756 cs.CV papers we have recorded · ↑ newer: Beyond Omni: A Unified MLLM for Embodied Sensory Understanding · ↓ older: StopWatch: Goal Grounding for Object-goal Navigation
Cite this page: Learning to Correct Geometry in Generated Videos: the #231 most recent of 756 cs.CV papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/learning-to-correct-geometry-in-generated-videos.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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