8 papers · 1 filter
MobileVLA-R1 2.0: RL-Enhanced Reasoning for Mobile Robot Control
Ting Huang, Yue Huang, Zeyu Zhang +2
Grounding natural-language instructions into reliable and executable actions remains a fundamental challenge for vision-language-action (VLA) systems on mobile robots, due to the p…
ConsiSpace: Learning Geometric Consistency Matters for Video Spatial Reasoning
Ting Huang, Zhenyu Zhang, Wenyuan Huang +2
Video spatial reasoning is essential for navigation-oriented perception and long-video question answering, where models must infer spatial relations across long horizons under chan…
Let Geometry GUIDE: Layer-wise Unrolling of Geometric Priors in Multimodal LLMs
Chongyu Wang, Ting Huang, Chunyu Sun +3
Multimodal Large Language Models (MLLMs) have achieved remarkable progress in 2D visual tasks but still struggle to understand physical space in real-world visual streams. Recently…
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…
OpenGround: Planning-based Online Perception for Open-World 3D Visual Grounding
Wenyuan Huang, Zhenyu Zhang, Zhao Wang +4
3D visual grounding aims to locate objects based on natural language descriptions in 3D scenes. Existing supervised methods are limited by generalization and recent zero-shot metho…
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…