- Abstract:
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It is not always possible to recognise objects and infer material properties for a scene from visual cues alone, since objects can look visually similar whilst being made of very different materials. In this paper, we therefore present an approach that augments the available dense visual cues with sparse auditory cues in order to estimate dense object and material labels. Since estimates of object class and material properties are mutually-informative, we optimise our multi-output labelling j...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's version
- Files:
-
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(pdf, 8.0mb)
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- Publisher copy:
- 10.5244/C.29.40
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- Publisher:
- BMVA Press Publisher's website
- Volume:
- abs/1601.02220
- Publication date:
- 2015-09-10
- DOI:
- URN:
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uuid:118d2199-a58e-45d3-9516-8c222ecd23e3
- Source identifiers:
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589583
- Local pid:
- pubs:589583
- Copyright holder:
- Arnab et al.
- Copyright date:
- 2015
- Notes:
- © 2015. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.
Conference
Joint object-material category segmentation from audio-visual cues
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Technicolor
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Engineering and Physical Sciences Research Council
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Leverhulme Trust
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