13 citations · 17 across the 19 of their papers we have counts for
20 papers
Robot Tool Design from Scratch via Behavior-Aware Hierarchical Optimization
Yinghan Chen, Xiyao Tian, Yizan Dai +2
The ability to design a tool for a task marks a level of intelligence beyond merely understanding, selecting, or using one. Existing methods for robotic tool design typically optim…
A Change of Frame Makes the Capture Point Proprioceptive: Distillation-Free Humanoid Single-Leg Balance
Yikai Zhou, Xingyun Wang, Jieming Cui +4
Unified humanoid policies track agile whole-body motion, yet few can hold a clean single-leg stance. On the single-leg balance benchmark introduced here, eight released state-of-th…
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…
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…
UniAct: Unified Motion Generation and Action Streaming for Humanoid Robots
Nan Jiang, Zimo He, Wanhe Yu +8
A long-standing objective in humanoid robotics is the realization of versatile agents capable of following diverse multimodal instructions with human-level flexibility. Despite adv…
Simultaneous Tactile-Visual Perception for Learning Multimodal Robot Manipulation
Yuyang Li, Yinghan Chen, Zihang Zhao +4
Robotic manipulation requires both rich multimodal perception and effective learning frameworks to handle complex real-world tasks. See-through-skin (STS) sensors, which combine ta…
Ag2x2: Robust Agent-Agnostic Visual Representations for Zero-Shot Bimanual Manipulation
Ziyin Xiong, Yinghan Chen, Puhao Li +3
Bimanual manipulation, fundamental to human daily activities, remains a challenging task due to its inherent complexity of coordinated control. Recent advances have enabled zero-sh…
CLONE: Closed-Loop Whole-Body Humanoid Teleoperation for Long-Horizon Tasks
Yixuan Li, Yutang Lin, Jieming Cui +4
Humanoid teleoperation plays a vital role in demonstrating and collecting data for complex humanoid-scene interactions. However, current teleoperation systems face critical limitat…
GROVE: A Generalized Reward for Learning Open-Vocabulary Physical Skill
Jieming Cui, Tengyu Liu, Ziyu Meng +5
Learning open-vocabulary physical skills for simulated agents presents a significant challenge in artificial intelligence. Current reinforcement learning approaches face critical l…
Dynamic Motion Blending for Versatile Motion Editing
Nan Jiang, Hongjie Li, Ziye Yuan +5
Text-guided motion editing enables high-level semantic control and iterative modifications beyond traditional keyframe animation. Existing methods rely on limited pre-collected tra…
Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations
Puhao Li, Tengyu Liu, Yuyang Li +6
Autonomous robotic systems capable of learning novel manipulation tasks are poised to transform industries from manufacturing to service automation. However, modern methods (e.g.,…
PhyRecon: Physically Plausible Neural Scene Reconstruction
Junfeng Ni, Yixin Chen, Bohan Jing +7
We address the issue of physical implausibility in multi-view neural reconstruction. While implicit representations have gained popularity in multi-view 3D reconstruction, previous…
Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordance
Zan Wang, Yixin Chen, Baoxiong Jia +7
Despite significant advancements in text-to-motion synthesis, generating language-guided human motion within 3D environments poses substantial challenges. These challenges stem pri…
AnySkill: Learning Open-Vocabulary Physical Skill for Interactive Agents
Jieming Cui, Tengyu Liu, Nian Liu +3
Traditional approaches in physics-based motion generation, centered around imitation learning and reward shaping, often struggle to adapt to new scenarios. To tackle this limitatio…
Scaling Up Dynamic Human-Scene Interaction Modeling
Nan Jiang, Zhiyuan Zhang, Hongjie Li +6
Confronting the challenges of data scarcity and advanced motion synthesis in human-scene interaction modeling, we introduce the TRUMANS dataset alongside a novel HSI motion synthes…
ProBio: A Protocol-guided Multimodal Dataset for Molecular Biology Lab
Jieming Cui, Ziren Gong, Baoxiong Jia +4
The challenge of replicating research results has posed a significant impediment to the field of molecular biology. The advent of modern intelligent systems has led to notable prog…
Single-view 3D Scene Reconstruction with High-fidelity Shape and Texture
Yixin Chen, Junfeng Ni, Nan Jiang +3
Reconstructing detailed 3D scenes from single-view images remains a challenging task due to limitations in existing approaches, which primarily focus on geometric shape recovery, o…
PartAfford: Part-level Affordance Discovery from 3D Objects
Chao Xu, Yixin Chen, He Wang +3
Understanding what objects could furnish for humans-namely, learning object affordance-is the crux to bridge perception and action. In the vision community, prior work primarily fo…
YouRefIt: Embodied Reference Understanding with Language and Gesture
Yixin Chen, Qing Li, Deqian Kong +5
We study the understanding of embodied reference: One agent uses both language and gesture to refer to an object to another agent in a shared physical environment. Of note, this ne…
Spatio-temporal Self-Supervised Representation Learning for 3D Point Clouds
Siyuan Huang, Yichen Xie, Song-Chun Zhu +1
To date, various 3D scene understanding tasks still lack practical and generalizable pre-trained models, primarily due to the intricate nature of 3D scene understanding tasks and t…