The DOI matches its Crossref record; 33 of the 35 references it cites were found in a registry or an index.
Is Faster R-CNN Doing Well for Pedestrian Detection?
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In the citing paper
“To this end, the bootstrap was reintroduced to object detection after 2016 [23, 38, 101, 102].”
From Object Detection in 20 Years: A Survey (2023) · cites this paper as [101]
In the citing paper
“In recent years, cascaded detection has been especially applied to those detection tasks of 'small objects in large scenes', e.g., face detection [126, 127], pedestrian detection [101, 124, 128], etc.”
From Object Detection in 20 Years: A Survey (2023) · cites this paper as [101]
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“[12], DPM [13, 15], RCNN [16], SPPNet [17], Fast RCNN [18], Faster RCNN [19], YOLO [20], SSD [21], FasterPed [165], OHEM [166], RetinaNet [23], RefineDet [55].”
BackgroundMethodInfluentialDeep Learning for Generic Object Detection: A Survey
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Metadata
- Authors
- Zhang, L., Lin, L., Liang, X., & He, K.
- Affiliations
- Sun Yat-sen University (CN)
- Microsoft Research Asia (China) (CN)
- Corresponding author
- Lin, Liang
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 443-457
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2497039038
- Cited by
- 852
- References
- 35
- Citations by year
- 2026: 5 · 2025: 21 · 2024: 41 · 2023: 68 · 2022: 81 · 2021: 122 · 2020: 121 · 2019: 152 · 2018: 150 · 2017: 87 · 2016: 4
- FWCI
- 45.47
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Natural Science Foundation of China (2016YFB1001000)
- Natural Science Foundation of Guangdong Province (S2013050014548)
- National Natural Science Foundation of China-Guangdong Joint Fund
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
- Keywords
- pedestrian detection, Faster R-CNN, region proposal network, small object detection, hard negative mining, object detection
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