collaborators

10 papers

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.RO2025

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…

cs.RO2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…