The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Hypercolumns for object segmentation and fine-grained localization
Abstract
Recognition algorithms based on convolutional networks (CNNs) typically use the output of the last layer as a feature representation. However, the information in this layer may be too coarse spatially to allow precise localization. On the contrary, earlier layers may be precise in localization but will not capture semantics. To get the best of both worlds, we define the hypercolumn at a pixel as the vector of activations of all CNN units above that pixel. Using hypercolumns as pixel descriptors, we show results on three fine-grained localization tasks: simultaneous detection and segmentation [22], where we improve state-of-the-art from 49.7 mean APr[22] to 60.0, keypoint localization, where we get a 3.3 point boost over [20], and part labeling, where we show a 6.6 point gain over a strong baseline.
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Do we really need more training data for object localization
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Metadata
- Authors
- Hariharan, B., Arbelaez, P., Girshick, R., & Malik, J.
- Affiliations
- University of California, Berkeley (US)
- Microsoft (United States) (US)
- Venue
- 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2015-06
- Pages
- 447-456
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W1948751323
- Cited by
- 1,511
- References
- 46
- Citations by year
- 2026: 28 · 2025: 37 · 2024: 58 · 2023: 101 · 2022: 100 · 2021: 159 · 2020: 179 · 2019: 222 · 2018: 220 · 2017: 225 · 2016: 138 · 2015: 42
- FWCI
- 85.45
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- hypercolumns, object segmentation, fine-grained localization, convolutional neural networks, keypoint detection
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