14 citations · 17 across the 5 of their papers we have counts for
5 papers
SPOT: SE(3) Pose Trajectory Diffusion for Object-Centric Manipulation
Cheng-Chun Hsu, Bowen Wen, Jie Xu +5
We introduce SPOT, an object-centric imitation learning framework. The key idea is to capture each task by an object-centric representation, specifically the SE(3) object pose traj…
KinScene: Model-Based Mobile Manipulation of Articulated Scenes
Cheng-Chun Hsu, Ben Abbatematteo, Zhenyu Jiang +3
Sequentially interacting with articulated objects is crucial for a mobile manipulator to operate effectively in everyday environments. To enable long-horizon tasks involving articu…
Ditto in the House: Building Articulation Models of Indoor Scenes through Interactive Perception
Cheng-Chun Hsu, Zhenyu Jiang, Yuke Zhu
Virtualizing the physical world into virtual models has been a critical technique for robot navigation and planning in the real world. To foster manipulation with articulated objec…
Ditto: Building Digital Twins of Articulated Objects from Interaction
Zhenyu Jiang, Cheng-Chun Hsu, Yuke Zhu
Digitizing physical objects into the virtual world has the potential to unlock new research and applications in embodied AI and mixed reality. This work focuses on recreating inter…
Every Pixel Matters: Center-aware Feature Alignment for Domain Adaptive Object Detector
Cheng-Chun Hsu, Yi-Hsuan Tsai, Yen-Yu Lin +1
A domain adaptive object detector aims to adapt itself to unseen domains that may contain variations of object appearance, viewpoints or backgrounds. Most existing methods adopt fe…