57 citations · 202 across the 49 of their papers we have counts for
53 papers
GeoReader: Learning Latent Geometry for Spatial Reasoning in Vision-Language Models
Rong Li, Shijie Li, Jiangyong Huang +7
Vision-language models (VLMs) struggle with metric and multi-view relationships that remain implicit in RGB observations. Geometry foundation models recover this structure from RGB…
Trajectory-Level Automatic Curriculum Learning for Legged Locomotion on Unstructured Terrain
Rocky Liu, Tengyu Liu, Baoxiong Jia +4
Training locomotion policies for complex unstructured terrain requires a curriculum to avoid early exploration failures. However, since unstructured terrain lacks explicit difficul…
Towards Human-level Dexterous Teleoperation
Puhao Li, Zeyuan Chen, Yingying Wu +9
Humans routinely wield tools, swap grasps, and reposition objects within a single hand, seamlessly orchestrating contact transitions that span translation, reorientation, and finge…
LARA: Latent Action Representation Alignment for Vision-Language-Action Models
Mengya Liu, Baoxiong Jia, Jiangyong Huang +2
Visual-language action (VLA) models enable robots to predict actions directly from observations and language instructions, but their performance depends on large-scale, high-qualit…
Lifting Unlabeled Internet-level Data for 3D Scene Understanding
Yixin Chen, Yaowei Zhang, Huangyue Yu +9
Annotated 3D scene data is scarce and expensive to acquire, while abundant unlabeled videos are readily available on the internet. In this paper, we demonstrate that carefully desi…
OmniClone: Engineering a Robust, All-Rounder Whole-Body Humanoid Teleoperation System
Yixuan Li, Le Ma, Yutang Lin +8
Whole-body humanoid teleoperation enables humans to remotely control humanoid robots, serving as both a real-time operational tool and a scalable engine for collecting demonstratio…
ESPIRE: A Diagnostic Benchmark for Embodied Spatial Reasoning of Vision-Language Models
Yanpeng Zhao, Wentao Ding, Hongtao Li +2
A recent trend in vision-language models (VLMs) has been to enhance their spatial cognition for embodied domains. Despite progress, existing evaluations have been limited both in p…
3D-RFT: Reinforcement Fine-Tuning for Video-based 3D Scene Understanding
Xiongkun Linghu, Jiangyong Huang, Baoxiong Jia +1
Reinforcement Learning with Verifiable Rewards ( RLVR ) has emerged as a transformative paradigm for enhancing the reasoning capabilities of Large Language Models ( LLMs), yet its…
OmniXtreme: Breaking the Generality Barrier in High-Dynamic Humanoid Control
Yunshen Wang, Shaohang Zhu, Peiyuan Zhi +7
High-fidelity motion tracking serves as the ultimate litmus test for generalizable, human-level motor skills. However, current policies often hit a "generality barrier": as motion…
OmniTrack: General Motion Tracking via Physics-Consistent Reference
Yuhan Li, Peiyuan Zhi, Yunshen Wang +6
Learning motion tracking from rich human motion data is a foundational task for achieving general control in humanoid robots, enabling them to perform diverse behaviors. However, d…
LessMimic: Long-Horizon Humanoid Interaction with Unified Distance Field Representations
Yutang Lin, Jieming Cui, Yixuan Li +3
Humanoid robots that autonomously interact with physical environments over extended horizons represent a central goal of embodied intelligence. Existing approaches rely on referenc…
SceneWeaver: All-in-One 3D Scene Synthesis with an Extensible and Self-Reflective Agent
Yandan Yang, Baoxiong Jia, Shujie Zhang +1
Indoor scene synthesis has become increasingly important with the rise of Embodied AI, which requires 3D environments that are not only visually realistic but also physically plaus…
Learning Human-Humanoid Coordination for Collaborative Object Carrying
Yushi Du, Yixuan Li, Baoxiong Jia +5
Human-humanoid collaboration shows significant promise for applications in healthcare, domestic assistance, and manufacturing. While compliant robot-human collaboration has been ex…
SceneCOT: Eliciting Grounded Chain-of-Thought Reasoning in 3D Scenes
Xiongkun Linghu, Jiangyong Huang, Ziyu Zhu +2
Existing research on 3D Large Language Models (LLMs) still struggles to achieve grounded question-answering, primarily due to the under-exploration of the mechanism of human-like s…
VideoArtGS: Building Digital Twins of Articulated Objects from Monocular Video
Yu Liu, Baoxiong Jia, Ruijie Lu +5
Building digital twins of articulated objects from monocular video presents an essential challenge in computer vision, which requires simultaneous reconstruction of object geometry…
GWM: Towards Scalable Gaussian World Models for Robotic Manipulation
Guanxing Lu, Baoxiong Jia, Puhao Li +4
Training robot policies within a learned world model is trending due to the inefficiency of real-world interactions. The established image-based world models and policies have show…
Spatial-Temporal Multi-Scale Quantization for Flexible Motion Generation
Zan Wang, Jingze Zhang, Yixin Chen +3
Despite significant advancements in human motion generation, current motion representations, typically formulated as discrete frame sequences, still face two critical limitations:…
Move to Understand a 3D Scene: Bridging Visual Grounding and Exploration for Efficient and Versatile Embodied Navigation
Ziyu Zhu, Xilin Wang, Yixuan Li +9
Embodied scene understanding requires not only comprehending visual-spatial information that has been observed but also determining where to explore next in the 3D physical world.…
LEO-VL: Efficient Scene Representation for Scalable 3D Vision-Language Learning
Jiangyong Huang, Xiaojian Ma, Xiongkun Linghu +6
Developing vision-language models (VLMs) capable of understanding 3D scenes has been a longstanding research goal. Despite recent progress, 3D VLMs still struggle with spatial reas…
MetaScenes: Towards Automated Replica Creation for Real-world 3D Scans
Huangyue Yu, Baoxiong Jia, Yixin Chen +9
Embodied AI (EAI) research requires high-quality, diverse 3D scenes to effectively support skill acquisition, sim-to-real transfer, and generalization. Achieving these quality stan…
Learning a Unified Policy for Position and Force Control in Legged Loco-Manipulation
Peiyuan Zhi, Peiyang Li, Jianqin Yin +2
Robotic loco-manipulation tasks often involve contact-rich interactions with the environment, requiring the joint modeling of contact force and robot position. However, recent visu…
Masked Point-Entity Contrast for Open-Vocabulary 3D Scene Understanding
Yan Wang, Baoxiong Jia, Ziyu Zhu +1
Open-vocabulary 3D scene understanding is pivotal for enhancing physical intelligence, as it enables embodied agents to interpret and interact dynamically within real-world environ…
RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning
Haoran Geng, Feishi Wang, Songlin Wei +34
Data scaling and standardized evaluation benchmarks have driven significant advances in natural language processing and computer vision. However, robotics faces unique challenges i…
Unveiling the Mist over 3D Vision-Language Understanding: Object-centric Evaluation with Chain-of-Analysis
Jiangyong Huang, Baoxiong Jia, Yan Wang +5
Existing 3D vision-language (3D-VL) benchmarks fall short in evaluating 3D-VL models, creating a "mist" that obscures rigorous insights into model capabilities and 3D-VL tasks. Thi…