Conference item
Zero-shot category-level object pose estimation
- Abstract:
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Object pose estimation is an important component of most vision pipelines for embodied agents, as well as in 3D vision more generally. In this paper we tackle the problem of estimating the pose of novel object categories in a zero-shot manner. This extends much of the existing literature by removing the need for pose-labelled datasets or category-specific CAD models for training or inference. Specifically, we make the following contributions. First, we formalise the zero-shot, category-level ...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Access Document
- Files:
-
-
(Accepted manuscript, pdf, 10.4MB)
-
- Publisher copy:
- 10.1007/978-3-031-19842-7_30
Authors
Bibliographic Details
- Publisher:
- Springer Publisher's website
- Series:
- Lecture Notes in Computer Science
- Issue:
- 13699
- Pages:
- 516-532
- Publication date:
- 2022-10-23
- Event title:
- 17th European Conference on Computer Vision (ECCV 2022)
- Event location:
- Tel Aviv, Israel
- Event website:
- https://eccv2022.ecva.net/
- Event start date:
- 2022-10-23
- Event end date:
- 2022-10-27
- DOI:
- EISSN:
-
1611-3349
- ISSN:
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0302-9743
- ISBN:
- 9783031198410
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1314595
- Local pid:
- pubs:1314595
- Deposit date:
- 2023-01-23
Terms of use
- Copyright holder:
- Goodwin et al
- Copyright date:
- 2022
- Rights statement:
- © 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
- Notes:
- This paper was presented at the 17th European Conference on Computer Vision (ECCV 2022), 23rd-27th October 2022, Tel Aviv, Israel. This is the accepted manuscript version of the article. The final version is available online from Springer at: https://doi.org/10.1007/978-3-031-19842-7_30
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