3 citations · 5 across the 16 of their papers we have counts for
18 papers
The Neverwhere Visual Parkour Benchmark Suite
Ziyu Chen, Henghui Bao, Haoran Chang +12
State-of-the-art visual locomotion controllers are increasingly capable at handling complex visual environments, making evaluating their real-world performance before deployment in…
EgoPhys: Learning Generalizable Physics Models of Deformable Objects from Egocentric Video
Hyunjin Kim, Ri-Zhao Qiu, Guangqi Jiang +1
Humans naturally understand object physics through everyday interactions, but faithfully predicting complex deformable dynamics, such as elastic materials and fabrics, remains a ma…
ConTrack: Constrained Hand Motion Tracking with Adaptive Trade-off Control
Yutong Liang, Quanquan Peng, Ri-Zhao Qiu +1
Human demonstrations provide strong priors for robot manipulation, yet it is non-trivial to transfer them to execute on real robots due to the kinematic gap. In dexterous manipulat…
Long-Horizon Manipulation via Trace-Conditioned VLA Planning
Isabella Liu, An-Chieh Cheng, Rui Yan +7
Long-horizon manipulation remains challenging for vision-language-action (VLA) policies: real tasks are multi-step, progress-dependent, and brittle to compounding execution errors.…
EgoVerse: An Egocentric Human Dataset for Robot Learning from Around the World
Ryan Punamiya, Simar Kareer, Zeyi Liu +37
Robot learning increasingly depends on large and diverse data, yet robot data collection remains expensive and difficult to scale. Egocentric human data offer a promising alternati…
In-N-On: Scaling Egocentric Manipulation with in-the-wild and on-task Data
Xiongyi Cai, Ri-Zhao Qiu, Geng Chen +5
Egocentric videos are a valuable and scalable data source to learn manipulation policies. However, due to significant data heterogeneity, most existing approaches utilize human dat…
HMC: Learning Heterogeneous Meta-Control for Contact-Rich Loco-Manipulation
Lai Wei, Xuanbin Peng, Ri-Zhao Qiu +3
Learning from real-world robot demonstrations holds promise for interacting with complex real-world environments. However, the complexity and variability of interaction dynamics of…
Gaussian-Augmented Physics Simulation and System Identification with Complex Colliders
Federico Vasile, Ri-Zhao Qiu, Lorenzo Natale +1
System identification involving the geometry, appearance, and physical properties from video observations is a challenging task with applications in robotics and graphics. Recent a…
GSWorld: Closed-Loop Photo-Realistic Simulation Suite for Robotic Manipulation
Guangqi Jiang, Haoran Chang, Ri-Zhao Qiu +6
This paper presents GSWorld, a robust, photo-realistic simulator for robotics manipulation that combines 3D Gaussian Splatting with physics engines. Our framework advocates "closin…
ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training
Ge Yan, Jiyue Zhu, Yuquan Deng +8
This paper introduces ManiFlow, a visuomotor imitation learning policy for general robot manipulation that generates precise, high-dimensional actions conditioned on diverse visual…
AMO: Adaptive Motion Optimization for Hyper-Dexterous Humanoid Whole-Body Control
Jialong Li, Xuxin Cheng, Tianshu Huang +3
Humanoid robots derive much of their dexterity from hyper-dexterous whole-body movements, enabling tasks that require a large operational workspace: such as picking objects off the…
Visual Acoustic Fields
Yuelei Li, Hyunjin Kim, Fangneng Zhan +7
Objects produce different sounds when hit, and humans can intuitively infer how an object might sound based on its appearance and material properties. Inspired by this intuition, w…
M3: 3D-Spatial MultiModal Memory
Xueyan Zou, Yuchen Song, Ri-Zhao Qiu +4
We present 3D Spatial MultiModal Memory (M3), a multimodal memory system designed to retain information about medium-sized static scenes through video sources for visual perception…
Humanoid Policy ~ Human Policy
Ri-Zhao Qiu, Shiqi Yang, Xuxin Cheng +12
Training manipulation policies for humanoid robots with diverse data enhances their robustness and generalization across tasks and platforms. However, learning solely from robot de…
WildLMa: Long Horizon Loco-Manipulation in the Wild
Ri-Zhao Qiu, Yuchen Song, Xuanbin Peng +8
'In-the-wild' mobile manipulation aims to deploy robots in diverse real-world environments, which requires the robot to (1) have skills that generalize across object configurations…
GraspSplats: Efficient Manipulation with 3D Feature Splatting
Mazeyu Ji, Ri-Zhao Qiu, Xueyan Zou +1
The ability for robots to perform efficient and zero-shot grasping of object parts is crucial for practical applications and is becoming prevalent with recent advances in Vision-La…
Feature Splatting: Language-Driven Physics-Based Scene Synthesis and Editing
Ri-Zhao Qiu, Ge Yang, Weijia Zeng +1
Scene representations using 3D Gaussian primitives have produced excellent results in modeling the appearance of static and dynamic 3D scenes. Many graphics applications, however,…
Learning Generalizable Feature Fields for Mobile Manipulation
Ri-Zhao Qiu, Yafei Hu, Yuchen Song +8
An open problem in mobile manipulation is how to represent objects and scenes in a unified manner so that robots can use both for navigation and manipulation. The latter requires c…