mlsanityData to 7 Oct 2026

CityPersons: A Diverse Dataset for Pedestrian Detection

arXiv 1702.05693 ↗First posted 19 Feb 2017cs.CVcited by 171

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Abstract (arXiv)

Convnets have enabled significant progress in pedestrian detection recently, but there are still open questions regarding suitable architectures and training data. We revisit CNN design and point out key adaptations, enabling plain FasterRCNN to obtain state-of-the-art results on the Caltech dataset. To achieve further improvement from more and better data, we introduce CityPersons, a new set of person annotations on top of the Cityscapes dataset. The diversity of CityPersons allows us for the first time to train one single CNN model that generalizes well over multiple benchmarks. Moreover, with additional training with CityPersons, we obtain top results using FasterRCNN on Caltech, improving especially for more difficult cases (heavy occlusion and small scale) and providing higher localization quality.

Key facts. Cited by 171 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Feb 2017.

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Citing papers per year: 2021: 32; 2022: 44; 2023: 42; 2024: 25; 2025: 16; 2026: 12.

171 papers.

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  1. 2021ByteTrack: Multi-Object Tracking by Associating Every Detection Boxcited by 812
  2. 2022DiffusionDet: Diffusion Model for Object Detectioncited by 354
  3. 2022StrongSORT: Make DeepSORT Great Againcited by 213
  4. 2021Occluded Video Instance Segmentation: A Benchmarkcited by 154
  5. 2023Vision Language Models in Autonomous Driving: A Survey and Outlookcited by 124
  6. 2023Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Taskscited by 94
  7. 2022Towards Grand Unification of Object Trackingcited by 93
  8. 2023TRACE: 5D Temporal Regression of Avatars with Dynamic Cameras in 3D Environmentscited by 89
  9. 2022SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videoscited by 80
  10. 2024CoVLA: Comprehensive Vision-Language-Action Dataset for Autonomous Drivingcited by 74
  11. 2021Multiple Object Tracking with Correlation Learningcited by 67
  12. 2024A Survey on Autonomous Driving Datasets: Statistics, Annotation Quality, and a Future Outlookcited by 65
38 more
  1. 2022QDTrack: Quasi-Dense Similarity Learning for Appearance-Only Multiple Object Trackingcited by 61
  2. 2023UniHCP: A Unified Model for Human-Centric Perceptionscited by 59
  3. 2021ROAD: The ROad event Awareness Dataset for Autonomous Drivingcited by 54
  4. 2021RelationTrack: Relation-aware Multiple Object Tracking with Decoupled Representationcited by 52
  5. 2023SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depthcited by 48
  6. 2021SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Drivingcited by 43
  7. 2021Anchor-Free Person Searchcited by 42
  8. 2021TransCenter: Transformers with Dense Representations for Multiple-Object Trackingcited by 42
  9. 2023HumanBench: Towards General Human-centric Perception with Projector Assisted Pretrainingcited by 38
  10. 2022Tracking Objects as Pixel-wise Distributionscited by 36
  11. 2022STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenescited by 35
  12. 2021INTERN: A New Learning Paradigm Towards General Visioncited by 33
  13. 2022Progressive End-to-End Object Detection in Crowded Scenescited by 31
  14. 2022SMILEtrack: SiMIlarity LEarning for Occlusion-Aware Multiple Object Trackingcited by 29
  15. 2021GAIA: A Transfer Learning System of Object Detection that Fits Your Needscited by 27
  16. 2022Weakly Aligned Feature Fusion for Multimodal Object Detectioncited by 26
  17. 2021One More Check: Making "Fake Background" Be Tracked Againcited by 25
  18. 2023Focus On Details: Online Multi-object Tracking with Diverse Fine-grained Representationcited by 25
  19. 2022Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmarkcited by 24
  20. 2023Hulk: A Universal Knowledge Translator for Human-Centric Taskscited by 22
  21. 2022Bamboo: Building Mega-Scale Vision Dataset Continually with Human-Machine Synergycited by 20
  22. 2023ByteTrackV2: 2D and 3D Multi-Object Tracking by Associating Every Detection Boxcited by 20
  23. 2023OmniTracker: Unifying Object Tracking by Tracking-with-Detectioncited by 19
  24. 2023VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervisioncited by 19
  25. 2022Object Localization under Single Coarse Point Supervisioncited by 18
  26. 2024Delving into the Trajectory Long-tail Distribution for Muti-object Trackingcited by 18
  27. 2022Online Multi-Object Tracking with Unsupervised Re-Identification Learning and Occlusion Estimationcited by 16
  28. 2022Towards Domain Generalization in Object Detectioncited by 16
  29. 2022Detection Recovery in Online Multi-Object Tracking with Sparse Graph Trackercited by 15
  30. 2021Degrade is Upgrade: Learning Degradation for Low-light Image Enhancementcited by 13
  31. 2022Deep Learning Serves Traffic Safety Analysis: A Forward-looking Reviewcited by 13
  32. 2024Crowd-SAM: SAM as a Smart Annotator for Object Detection in Crowded Scenescited by 13
  33. 2022Amodal Cityscapes: A New Dataset, its Generation, and an Amodal Semantic Segmentation Challenge Baselinecited by 12
  34. 2023DeNoising-MOT: Towards Multiple Object Tracking with Severe Occlusionscited by 12
  35. 2021A Multi-viewpoint Outdoor Dataset for Human Action Recognitioncited by 11
  36. 2023Towards More Practical Group Activity Detection: A New Benchmark and Modelcited by 11
  37. 2021Variational Pedestrian Detectioncited by 10
  38. 2024When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark Datasetcited by 10

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