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cs.CV2026

PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies

Haitao Lin, Hanyang Yu, Jingshun Huang +5

Existing Vision-Language-Action (VLA) models often suffer from feature collapse and low training efficiency because they entangle high-level perception with sparse, embodiment-spec…

cs.CV2026

MVGGT: Multimodal Visual Geometry Grounded Transformer for Multiview 3D Referring Expression Segmentation

Changli Wu, Haodong Wang, Jiayi Ji +5

Most existing 3D referring expression segmentation (3DRES) methods rely on dense, high-quality point clouds, while real-world agents such as robots and mobile phones operate with o…

cs.CV2026

Mind-of-Director: Multi-modal Agent-Driven Film Previsualization via Collaborative Decision-Making

Shufeng Nan, Mengtian Li, Sixiao Zheng +3

We present Mind-of-Director, a multi-modal agent-driven framework for film previz that models the collaborative decision-making process of a film production team. Given a creative…

cs.CV2026

VerseCrafter: Dynamic Realistic Video World Model with 4D Geometric Control

Sixiao Zheng, Minghao Yin, Wenbo Hu +3

Video world models aim to simulate dynamic, real-world environments, yet existing methods struggle to provide unified and precise control over camera and multi-object motion, as vi…

cs.CV2025

ReVSeg: Incentivizing the Reasoning Chain for Video Segmentation with Reinforcement Learning

Yifan Li, Yingda Yin, Lingting Zhu +4

Reasoning-centric video object segmentation is an inherently complex task: the query often refers to dynamics, causality, and temporal interactions, rather than static appearances.…

cs.CV2025

Enhancing Video Inpainting with Aligned Frame Interval Guidance

Ming Xie, Junqiu Yu, Qiaole Dong +2

Recent image-to-video (I2V) based video inpainting methods have made significant strides by leveraging single-image priors and modeling temporal consistency across masked frames. N…