A CNN cascade for landmark guided semantic part segmentation
This paper proposes a CNN cascade for semantic part segmentation guided by pose-specifc information encoded in terms of a set of landmarks (or keypoints). There is large amount of prior work on each of these tasks separately, yet, to the best of our knowledge, this is the first time in literature th...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
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2016
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| Online Access: | https://eprints.nottingham.ac.uk/37234/ |
| _version_ | 1848795418935164928 |
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| author | Jackson, Aaron S. Valstar, Michel Tzimiropoulos, Georgios |
| author_facet | Jackson, Aaron S. Valstar, Michel Tzimiropoulos, Georgios |
| author_sort | Jackson, Aaron S. |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | This paper proposes a CNN cascade for semantic part segmentation guided by pose-specifc information encoded in terms of a set of landmarks (or keypoints). There is large amount of prior work on each of these tasks separately, yet, to the best of our knowledge, this is the first time in literature that the interplay between pose estimation and semantic part segmentation is investigated. To address this limitation of prior work, in this paper, we propose a CNN cascade of tasks that firstly performs landmark localisation and then uses this information as input for guiding semantic part segmentation. We applied our architecture to the problem of facial part segmentation and report large performance improvement over the standard unguided network on the most challenging face datasets. Testing code and models will be published online at http://cs.nott.ac.uk/~psxasj/. |
| first_indexed | 2025-11-14T19:31:47Z |
| format | Conference or Workshop Item |
| id | nottingham-37234 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:31:47Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-372342020-05-04T18:17:41Z https://eprints.nottingham.ac.uk/37234/ A CNN cascade for landmark guided semantic part segmentation Jackson, Aaron S. Valstar, Michel Tzimiropoulos, Georgios This paper proposes a CNN cascade for semantic part segmentation guided by pose-specifc information encoded in terms of a set of landmarks (or keypoints). There is large amount of prior work on each of these tasks separately, yet, to the best of our knowledge, this is the first time in literature that the interplay between pose estimation and semantic part segmentation is investigated. To address this limitation of prior work, in this paper, we propose a CNN cascade of tasks that firstly performs landmark localisation and then uses this information as input for guiding semantic part segmentation. We applied our architecture to the problem of facial part segmentation and report large performance improvement over the standard unguided network on the most challenging face datasets. Testing code and models will be published online at http://cs.nott.ac.uk/~psxasj/. 2016-10-07 Conference or Workshop Item PeerReviewed Jackson, Aaron S., Valstar, Michel and Tzimiropoulos, Georgios (2016) A CNN cascade for landmark guided semantic part segmentation. In: ECCV 2016 Workshop, Geometry meets Deep Learning, 9 October 2016, Amsterdam, Netherlands. pose estimation landmark localisation semantic part seg- mentation faces |
| spellingShingle | pose estimation landmark localisation semantic part seg- mentation faces Jackson, Aaron S. Valstar, Michel Tzimiropoulos, Georgios A CNN cascade for landmark guided semantic part segmentation |
| title | A CNN cascade for landmark guided semantic part segmentation |
| title_full | A CNN cascade for landmark guided semantic part segmentation |
| title_fullStr | A CNN cascade for landmark guided semantic part segmentation |
| title_full_unstemmed | A CNN cascade for landmark guided semantic part segmentation |
| title_short | A CNN cascade for landmark guided semantic part segmentation |
| title_sort | cnn cascade for landmark guided semantic part segmentation |
| topic | pose estimation landmark localisation semantic part seg- mentation faces |
| url | https://eprints.nottingham.ac.uk/37234/ |