no code implementations • 3 Oct 2022 • Stanley Lewis, Jana Pavlasek, Odest Chadwicke Jenkins
We show the applicability of the model to gradient-based inference methods through a configuration estimation and 6 degree-of-freedom pose refinement task.
1 code implementation • 1 Mar 2022 • Xiaotong Chen, Huijie Zhang, Zeren Yu, Stanley Lewis, Odest Chadwicke Jenkins
We demonstrate the effectiveness of ProgressLabeller by rapidly create a dataset of over 1M samples with which we fine-tune a state-of-the-art pose estimation network in order to markedly improve the downstream robotic grasp success rates.
no code implementations • 6 Aug 2020 • Jana Pavlasek, Stanley Lewis, Karthik Desingh, Odest Chadwicke Jenkins
To address this problem, we present a generative-discriminative parts-based recognition and localization method for articulated objects in clutter.