Paper page - WorldCast: World-Consistent Character Video Generation with Large-Angle Camera Control

Source: https://huggingface.co/papers/2610.33135

Abstract

CLACT and WorldCast enable consistent character video generation under large-angle camera motions by combining 3D point-cloud guidance with geometry-aligned memory attention.

Precise camera control is essential for cinematic character video generation, yet existing methods struggle to follow large-angle trajectories with combined rotation, translation, and radius variation from arbitrary initial azimuths. Such viewpoint changes also reveal character regions unseen in the initial frame, causing geometric distortions, appearance degradation, and identity drift. To systematically study these coupled challenges, we introduceCLACT, a large-scale Character-centric dataset and benchmark covering diverse Large-Angle Camera Trajectories, with accurate camera geometry and multi-view character observations for training and evaluation. We further proposeWorldCast, a framework for world-consistent character video generation under diverse large-angle camera motions. Specifically, we back-project the initial frame into a3D point cloudusing estimated depth, align the point-cloud scale with the targetcamera trajectory, and render it along the trajectory to obtain explicit geometric guidance and coverage masks. To complement the incomplete character information, we introduceGeometry-Aligned Memory Attention(GAMA). Usingrelative camera posesestimated jointly from the initial frame andmulti-view character anchors, we express anchor and target-view geometry in a common coordinate frame.GAMAuses this geometric alignment to guide the retrieval and injection of view-relevant character features during generation. Evaluations across diverse large-angle camera trajectories demonstrate accurate trajectory following while preserving character geometry, appearance, and identity.

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