6 papers
3D CoCa v2: Contrastive Learners with Test-Time Search for Generalizable Spatial Intelligence
Hao Tang, Ting Huang, Zeyu Zhang
Spatial intelligence refers to the ability to perceive, reason about, and describe objects and their relationships within three-dimensional environments, forming a foundation for e…
MobileVLA-R1: Reinforcing Vision-Language-Action for Mobile Robots
Ting Huang, Dongjian Li, Rui Yang +3
Grounding natural-language instructions into continuous control for quadruped robots remains a fundamental challenge in vision language action. Existing methods struggle to bridge…
Nav-R1: Reasoning and Navigation in Embodied Scenes
Qingxiang Liu, Ting Huang, Zeyu Zhang +1
Embodied navigation requires agents to integrate perception, reasoning, and action for robust interaction in complex 3D environments. Existing approaches often suffer from incohere…
3D-R1: Enhancing Reasoning in 3D VLMs for Unified Scene Understanding
Ting Huang, Zeyu Zhang, Hao Tang
Large vision-language models (VLMs) have made significant strides in 2D visual understanding tasks, sparking interest in extending these capabilities to 3D scene understanding. How…
DC-Scene: Data-Centric Learning for 3D Scene Understanding
Ting Huang, Zeyu Zhang, Ruicheng Zhang +1
3D scene understanding plays a fundamental role in vision applications such as robotics, autonomous driving, and augmented reality. However, advancing learning-based 3D scene under…
3D CoCa: Contrastive Learners are 3D Captioners
Ting Huang, Zeyu Zhang, Yemin Wang +1
3D captioning, which aims to describe the content of 3D scenes in natural language, remains highly challenging due to the inherent sparsity of point clouds and weak cross-modal ali…