1.3k citations · 2.1k across the 27 of their papers we have counts for
29 papers
BOP Challenge 2024 on Model-Based and Model-Free 6D Object Pose Estimation
Van Nguyen Nguyen, Stephen Tyree, Andrew Guo +16
We present the evaluation methodology, datasets and results of the BOP Challenge 2024, the 6th in a series of public competitions organized to capture the state of the art in 6D ob…
RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics
Chan Hee Song, Valts Blukis, Jonathan Tremblay +3
Spatial understanding is a crucial capability that enables robots to perceive their surroundings, reason about their environment, and interact with it meaningfully. In modern robot…
Diff-DOPE: Differentiable Deep Object Pose Estimation
Jonathan Tremblay, Bowen Wen, Valts Blukis +3
We introduce Diff-DOPE, a 6-DoF pose refiner that takes as input an image, a 3D textured model of an object, and an initial pose of the object. The method uses differentiable rende…
HANDAL: A Dataset of Real-World Manipulable Object Categories with Pose Annotations, Affordances, and Reconstructions
Andrew Guo, Bowen Wen, Jianhe Yuan +4
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 t…
BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects
Bowen Wen, Jonathan Tremblay, Valts Blukis +6
We present a near real-time method for 6-DoF tracking of an unknown object from a monocular RGBD video sequence, while simultaneously performing neural 3D reconstruction of the obj…
MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare
Yann Labbé, Lucas Manuelli, Arsalan Mousavian +7
We introduce MegaPose, a method to estimate the 6D pose of novel objects, that is, objects unseen during training. At inference time, the method only assumes knowledge of (i) a reg…