The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Pedestrian Attribute Recognition At Far Distance
Abstract
The capability of recognizing pedestrian attributes, such as gender and clothing style, at far distance, is of practical interest in far-view surveillance scenarios where face and body close-shots are hardly available. We make two contributions in this paper. First, we release a new pedestrian attribute dataset, which is by far the largest and most diverse of its kind. We show that the large-scale dataset facilitates the learning of robust attribute detectors with good generalization performance. Second, we present the benchmark performance by SVM-based method and propose an alternative approach that exploits context of neighboring pedestrian images for improved attribute inference.
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Learning Color Names for Real-World Applications
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Cosegmentation of Image Pairs by Histogram Matching - Incorporating a Global Constraint into MRFs
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Person Re-identification by Attributes
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Cited by
HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis
Liu, X., Zhao, H., Tian, M., Sheng, L., Shao, J., Yi, S., Yan, J., & Wang, X. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.46 · Cited by 567
A survey on few-shot class-incremental learning
Tian, S., Li, L., Li, W., Ran, H., Ning, X., & Tiwari, P. (2024) · Neural Networks · doi:10.1016/j.neunet.2023.10.039 · Cited by 220
Detecting 32 Pedestrian Attributes for Autonomous Vehicles
Mordan, T., Cord, M., Perez, P., & Alahi, A. (2022) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2021.3107587 · Cited by 36
Metadata
- Authors
- DENG, Y., Luo, P., Loy, C. C., & Tang, X.
- Venue
- Proceedings of the 22nd ACM international conference on Multimedia
- Publisher
- ACM
- Published
- 2014-11-03
- Pages
- 789-792
- OpenAlex
- W2111025459
- Cited by
- 448
- References
- 20
- FWCI
- 11.53
- Type
- conference paper
- Language
- en
- Open access
- closed
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- DENG, Y., Luo, P., Loy, C. C., & Tang, X. (2014). Pedestrian Attribute Recognition At Far Distance. Proceedings of the 22nd ACM international conference on Multimedia. https://doi.org/10.1145/2647868.2654966
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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