APEX: Unsupervised, object-centric scene segmentation and tracking for robot manipulation
Recent advances in unsupervised learning for object detection, segmentation, and tracking hold significant promise for applications in robotics. A common approach is to frame these tasks as inference in probabilistic latent-variable models. In this paper, however, we show that the current state-of-t...
| 主要な著者: | , , , |
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| フォーマット: | Conference item |
| 言語: | English |
| 出版事項: |
Institute of Electrical and Electronics Engineers
2021
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