The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Beyond Bounding-Box: Convex-hull Feature Adaptation for Oriented and Densely Packed Object Detection
Abstract
Detecting oriented and densely packed objects remains challenging for spatial feature aliasing caused by the intersection of reception fields between objects. In this paper, we propose a convex-hull feature adaptation (CFA) approach for configuring convolutional features in accordance with oriented and densely packed object layouts. CFA is rooted in convex-hull feature representation, which defines a set of dynamically predicted feature points guided by the convex intersection over union (CIoU) to bound the extent of objects. CFA pursues optimal feature assignment by constructing convex-hull sets and dynamically splitting positive or negative convex-hulls. By simultaneously considering overlapping convex-hulls and objects and penalizing convex-hulls shared by multiple objects, CFA alleviates spatial feature aliasing towards optimal feature adaptation. Experiments on DOTA and SKU110K-R datasets show that CFA significantly outperforms the baseline approach, achieving new state-of-the-art detection performance. Code is available at github.com/SDL-GuoZonghao/BeyondBoundingBox.
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Cites
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“For example, the SIFT features [22], Gabor features [8], and LBP [23] used orientation-encoded feature channels or bit cyclic shift to achieve rotation in-variance.”
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Cited by
Large Selective Kernel Network for Remote Sensing Object Detection
Li, Y., Hou, Q., Zheng, Z., Cheng, M.-M., Yang, J., & Li, X. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01540 · Cited by 893
Metadata
- Authors
- Guo, Z., Liu, C., Zhang, X., Jiao, J., Ji, X., & Ye, Q.
- Venue
- 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2021-06
- Pages
- 8788-8797
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W3173658130
- Cited by
- 258
- References
- 43
- FWCI
- 14.21
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Guo, Z., Liu, C., Zhang, X., Jiao, J., Ji, X., & Ye, Q. (2021). Beyond Bounding-Box: Convex-hull Feature Adaptation for Oriented and Densely Packed Object Detection. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr46437.2021.00868
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