20 papers
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…
Schrödinger's Navigator: Imagining an Ensemble of Futures for Zero-Shot Object Navigation
Yu He, Da Huang, Zhenyang Liu +5
Zero-shot object navigation (ZSON) requires robots to find target objects in unseen environments without task-specific fine-tuning or pre-built maps, a key capability for general-p…
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…
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…
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…
OCRA: Object-Centric Learning with 3D and Tactile Priors for Human-to-Robot Action Transfer
Kuanning Wang, Ke Fan, Yuqian Fu +6
We present OCRA, an Object-Centric framework for video-based human-to-Robot Action transfer that learns directly from human demonstration videos to enable robust manipulation. Obje…