1 code implementation • 6 Nov 2023 • Shiyang Lu, Haonan Chang, Eric Pu Jing, Abdeslam Boularias, Kostas Bekris
This work presents OVIR-3D, a straightforward yet effective method for open-vocabulary 3D object instance retrieval without using any 3D data for training.
Ranked #4 on 3D Open-Vocabulary Instance Segmentation on Replica
1 code implementation • 27 Sep 2023 • Haonan Chang, Kowndinya Boyalakuntla, Shiyang Lu, Siwei Cai, Eric Jing, Shreesh Keskar, Shijie Geng, Adeeb Abbas, Lifeng Zhou, Kostas Bekris, Abdeslam Boularias
We present an Open-Vocabulary 3D Scene Graph (OVSG), a formal framework for grounding a variety of entities, such as object instances, agents, and regions, with free-form text-based queries.
no code implementations • 9 Apr 2023 • Shiyang Lu, Yunfu Deng, Abdeslam Boularias, Kostas Bekris
This work proposes a self-supervised learning system for segmenting rigid objects in RGB images.
no code implementations • 29 Mar 2023 • Chaitanya Mitash, Fan Wang, Shiyang Lu, Vikedo Terhuja, Tyler Garaas, Felipe Polido, Manikantan Nambi
This paper introduces Amazon Robotic Manipulation Benchmark (ARMBench), a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse.
no code implementations • 13 Sep 2022 • Kun Wang, William R. Johnson III, Shiyang Lu, Xiaonan Huang, Joran Booth, Rebecca Kramer-Bottiglio, Mridul Aanjaneya, Kostas Bekris
This strategy is based on a differentiable physics engine that can be trained given limited data from a real robot.
no code implementations • 29 May 2022 • Shiyang Lu, William R. Johnson III, Kun Wang, Xiaonan Huang, Joran Booth, Rebecca Kramer-Bottiglio, Kostas Bekris
To ensure that the pose estimates of rigid elements are physically feasible, i. e., they are not resulting in collisions between rods or with the environment, physical constraints are introduced during the optimization.
no code implementations • 11 Aug 2020 • Rui Wang, Chaitanya Mitash, Shiyang Lu, Daniel Boehm, Kostas E. Bekris
This work proposes first a perception process for 6D pose estimation, which returns a discrete distribution of object poses in a scene.