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PointZero: 3D Point Track Completion for Learning Transferable 3D Dynamics

Paper recorded by Signals 4 on 2026-09-16 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-16 on arXiv · recorded by Signals 4 on 2026-09-17

Category: cs.CV · 计算机视觉 · first seen 2026-09-17

Abstract

World models endow perceptual systems with the ability to predict how scenes evolve under interaction. They are most beneficial when trained on diverse volumes of data, to instill a rich prior into downstream applications. Existing methods typically require robot action labels to learn action-conditioned 3D dynamics, which excludes web video data from the training pool. We study 3D point track com

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#16 most recent of 237 cs.CV papers we have recorded · ↑ newer: CoRef-GS: Cooperative Referring Gaussian Splatting for Multi-Agent Sce · ↓ older: In-Context Robot Learning with VLM Agents
Cite this page: PointZero: 3D Point Track Completion for Learning Transferable 3D Dynamics: the #16 most recent of 237 cs.CV papers we have recorded (as of 2026-09-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/pointzero-3d-point-track-completion-for-learning-transferable-3d-dynamics.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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