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cs.CV2026

Stable Curves, Unstable Items: Item-Level Scaling Heterogeneity in Video LLMs

Wenzhang Sun, Chunfeng Wang, Xiangchen Yin +3

Aggregate scaling curves suggest that Video LLMs improve smoothly or saturate as visual budgets grow. We show that this view can conceal large, opposing changes at the item level.…

cs.CV2026

Holo-World: Unified Camera, Object and Weather Control for Video World Model

Xiangchen Yin, Wenzhang Sun, Jiahui Yuan +6

Video world models are moving toward preserving an observed world under controllable camera and object motion while allowing its environmental state to change. Yet these controls r…

cs.CV2026

Preserve, Reveal, Expand: Faithful 4D Video Editing with Region-Aware Conditioning

Zhangchi Hu, Wenzhang Sun, Xiangchen Yin +5

Existing 4D-driven video diffusion models primarily target plausible generation, but faithful 4D editing requires preserving source-observed regions while synthesizing disoccluded…

cs.CV2026

MUSE: A Multi-agent Framework for Unconstrained Story Envisioning via Closed-Loop Cognitive Orchestration

Wenzhang Sun, Zhenyu Wang, Zhangchi Hu +3

Generating long-form audio-visual stories from a short user prompt remains challenging due to an intent-execution gap, where high-level narrative intent must be preserved across co…

cs.CV2025

DrivingScene: A Multi-Task Online Feed-Forward 3D Gaussian Splatting Method for Dynamic Driving Scenes

Qirui Hou, Wenzhang Sun, Chang Zeng +3

Real-time, high-fidelity reconstruction of dynamic driving scenes is challenged by complex dynamics and sparse views, with prior methods struggling to balance quality and efficienc…

cs.CV2025

PAGS: Priority-Adaptive Gaussian Splatting for Dynamic Driving Scenes

Ying A, Wenzhang Sun, Chang Zeng +3

Reconstructing dynamic 3D urban scenes is crucial for autonomous driving, yet current methods face a stark trade-off between fidelity and computational cost. This inefficiency stem…