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WorldForge V2: Eliciting Camera-Trajectory Alignment in Video Diffusion Models

Paper recorded by Signals 4 on 2026-10-22 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-22 on arXiv · recorded by Signals 4 on 2026-10-23

Category: cs.CV · 计算机视觉 · first seen 2026-10-23

Abstract

Video diffusion models have learned rich 3D/4D priors, making them promising for scene generation and video re-rendering. However, their use in spatial tasks is limited by imprecise camera control, spatial and temporal inconsistencies, and entangled camera motion with scene dynamics. Existing approaches, such as task-specific fine-tuning and post-process warping, often introduce visual artifacts,

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#179 most recent of 756 cs.CV papers we have recorded · ↑ newer: UniVOE: A Removal-Driven Framework for Interaction-Aware Universal Vid · ↓ older: HiP3R: Hierarchical Pose Graphs for Long-Horizon 3D Reconstruction
Cite this page: WorldForge V2: Eliciting Camera-Trajectory Alignment in Video Diffusion Models: the #179 most recent of 756 cs.CV papers we have recorded (as of 2026-10-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/worldforge-v2-eliciting-camera-trajectory-alignment-in-video-diffusion-models.html
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