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Foundationpose: Unified 6d pose estimation and tracking of novel objects
We present FoundationPose a unified foundation model for 6D object pose estimation and
tracking supporting both model-based and model-free setups. Our approach can be instantly …
tracking supporting both model-based and model-free setups. Our approach can be instantly …
Bundlesdf: Neural 6-dof tracking and 3d reconstruction of unknown objects
B Wen, J Tremblay, V Blukis, S Tyree… - Proceedings of the …, 2023 - openaccess.thecvf.com
We present a near real-time (10Hz) method for 6-DoF tracking of an unknown object from a
monocular RGBD video sequence, while simultaneously performing neural 3D …
monocular RGBD video sequence, while simultaneously performing neural 3D …
Mimicgen: A data generation system for scalable robot learning using human demonstrations
A Mandlekar, S Nasiriany, B Wen, I Akinola… - arxiv preprint arxiv …, 2023 - arxiv.org
Imitation learning from a large set of human demonstrations has proved to be an effective
paradigm for building capable robot agents. However, the demonstrations can be extremely …
paradigm for building capable robot agents. However, the demonstrations can be extremely …
Instance-adaptive and geometric-aware keypoint learning for category-level 6d object pose estimation
Category-level 6D object pose estimation aims to estimate the rotation translation and size
of unseen instances within specific categories. In this area dense correspondence-based …
of unseen instances within specific categories. In this area dense correspondence-based …
Industreal: Transferring contact-rich assembly tasks from simulation to reality
Robotic assembly is a longstanding challenge, requiring contact-rich interaction and high
precision and accuracy. Many applications also require adaptivity to diverse parts, poses …
precision and accuracy. Many applications also require adaptivity to diverse parts, poses …
Tta-cope: Test-time adaptation for category-level object pose estimation
T Lee, J Tremblay, V Blukis, B Wen… - Proceedings of the …, 2023 - openaccess.thecvf.com
Test-time adaptation methods have been gaining attention recently as a practical solution for
addressing source-to-target domain gaps by gradually updating the model without requiring …
addressing source-to-target domain gaps by gradually updating the model without requiring …
Se (3)-equivariant relational rearrangement with neural descriptor fields
A Simeonov, Y Du, YC Lin, AR Garcia… - … on Robot Learning, 2023 - proceedings.mlr.press
We present a framework for specifying tasks involving spatial relations between objects
using only 5-10 demonstrations and then executing such tasks given point cloud …
using only 5-10 demonstrations and then executing such tasks given point cloud …
Vision-based manipulation from single human video with open-world object graphs
We present an object-centric approach to empower robots to learn vision-based
manipulation skills from human videos. We investigate the problem of imitating robot …
manipulation skills from human videos. We investigate the problem of imitating robot …
Handal: A dataset of real-world manipulable object categories with pose annotations, affordances, and reconstructions
A Guo, B Wen, J Yuan, J Tremblay… - 2023 IEEE/RSJ …, 2023 - ieeexplore.ieee.org
We present the HANDAL dataset for category-level object pose estimation and affordance
prediction. Unlike previous datasets, ours is focused on robotics-ready manipulable objects …
prediction. Unlike previous datasets, ours is focused on robotics-ready manipulable objects …
Frame mining: a free lunch for learning robotic manipulation from 3d point clouds
We study how choices of input point cloud coordinate frames impact learning of
manipulation skills from 3D point clouds. There exist a variety of coordinate frame choices to …
manipulation skills from 3D point clouds. There exist a variety of coordinate frame choices to …