5 papers
GTR: Gaussian Splatting Tracking and Reconstruction of Unknown Objects Based on Appearance and Geometric Complexity
Takuya Ikeda, Sergey Zakharov, Muhammad Zubair Irshad +8
We present a novel method for 6-DoF object tracking and high-quality 3D reconstruction from monocular RGBD video. Existing methods, while achieving impressive results, often strugg…
ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Grasping
Shun Iwase, Zubair Irshad, Katherine Liu +8
Robotic grasping is a cornerstone capability of embodied systems. Many methods directly output grasps from partial information without modeling the geometry of the scene, leading t…
DiffusionNOCS: Managing Symmetry and Uncertainty in Sim2Real Multi-Modal Category-level Pose Estimation
Takuya Ikeda, Sergey Zakharov, Tianyi Ko +5
This paper addresses the challenging problem of category-level pose estimation. Current state-of-the-art methods for this task face challenges when dealing with symmetric objects a…
Gravity-aware Grasp Generation with Implicit Grasp Mode Selection for Underactuated Hands
Tianyi Ko, Takuya Ikeda, Thomas Stewart +2
Learning-based grasp detectors typically assume a precision grasp, where each finger only has one contact point, and estimate the grasp probability. In this work, we propose a data…
GS-Pose: Category-Level Object Pose Estimation via Geometric and Semantic Correspondence
Pengyuan Wang, Takuya Ikeda, Robert Lee +1
Category-level pose estimation is a challenging task with many potential applications in computer vision and robotics. Recently, deep-learning-based approaches have made great prog…