mlsanityData to 7 Oct 2026

Object detection via a multi-region & semantic segmentation-aware CNN model

arXiv 1505.01749 ↗First posted 7 May 2015cs.CV cs.LG cs.NEcited by 47

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Abstract (arXiv)

We propose an object detection system that relies on a multi-region deep convolutional neural network (CNN) that also encodes semantic segmentation-aware features. The resulting CNN-based representation aims at capturing a diverse set of discriminative appearance factors and exhibits localization sensitivity that is essential for accurate object localization. We exploit the above properties of our recognition module by integrating it on an iterative localization mechanism that alternates between scoring a box proposal and refining its location with a deep CNN regression model. Thanks to the efficient use of our modules, we detect objects with very high localization accuracy. On the detection challenges of PASCAL VOC2007 and PASCAL VOC2012 we achieve mAP of 78.2% and 73.9% correspondingly, surpassing any other published work by a significant margin.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 May 2015.

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Citing papers per year: 2021: 15; 2022: 12; 2023: 8; 2024: 8; 2025: 4.

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  1. 2021Pre-Trained Models: Past, Present and Futurecited by 319
  2. 2021RangeDet:In Defense of Range View for LiDAR-based 3D Object Detectioncited by 140
  3. 2022Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmarkcited by 56
  4. 2021Large-Scale Unsupervised Object Discoverycited by 54
  5. 2023Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detectioncited by 43
  6. 2021Sequential End-to-end Network for Efficient Person Searchcited by 38
  7. 2022Rank-based Decomposable Losses in Machine Learning: A Surveycited by 26
  8. 2021Sum of Ranked Range Loss for Supervised Learningcited by 23
  9. 2021Recurrent Glimpse-based Decoder for Detection with Transformercited by 21
  10. 2022Active Learning Strategies for Weakly-supervised Object Detectioncited by 17
  11. 2021Hallucination In Object Detection -- A Study In Visual Part Verificationcited by 16
  12. 2024Progressive Pretext Task Learning for Human Trajectory Predictioncited by 16
35 more
  1. 2021Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detectioncited by 13
  2. 2021Certifiably Robust Interpretation via Renyi Differential Privacycited by 10
  3. 2022Boosting R-CNN: Reweighting R-CNN Samples by RPN's Error for Underwater Object Detectioncited by 10
  4. 2022CenterNet++ for Object Detectioncited by 9
  5. 2021CE-FPN: Enhancing Channel Information for Object Detectioncited by 8
  6. 20223D Cascade RCNN: High Quality Object Detection in Point Cloudscited by 7
  7. 2023PrObeD: Proactive Object Detection Wrappercited by 7
  8. 2021CRFace: Confidence Ranker for Model-Agnostic Face Detection Refinementcited by 6
  9. 2022EResFD: Rediscovery of the Effectiveness of Standard Convolution for Lightweight Face Detectioncited by 5
  10. 2022Transformer-based Context Condensation for Boosting Feature Pyramids in Object Detectioncited by 5
  11. 2023Spatio-Temporal Point Process for Multiple Object Trackingcited by 5
  12. 2025VISLIX: An XAI Framework for Validating Vision Models with Slice Discovery and Analysiscited by 5
  13. 2021Towards Full-to-Empty Room Generation with Structure-Aware Feature Encoding and Soft Semantic Region-Adaptive Normalizationcited by 4
  14. 2022Evaluating Context for Deep Object Detectorscited by 4
  15. 2023AMD: Adaptive Masked Distillation for Object Detectioncited by 4
  16. 2021Improving Apparel Detection with Category Grouping and Multi-grained Branchescited by 3
  17. 2021A Survey on Deep Domain Adaptation and Tiny Object Detection Challenges, Techniques and Datasetscited by 3
  18. 2023Frame Fusion with Vehicle Motion Prediction for 3D Object Detectioncited by 3
  19. 2023Progressive Recurrent Network for Shadow Removalcited by 3
  20. 2024Adaptive Hierarchical Certification for Segmentation using Randomized Smoothingcited by 3
  21. 2021V2F-Net: Explicit Decomposition of Occluded Pedestrian Detectioncited by 2
  22. 2023Enhancing Your Trained DETRs with Box Refinementcited by 2
  23. 2022SODAR: Segmenting Objects by DynamicallyAggregating Neighboring Mask Representationscited by 1
  24. 2022Seismic-phase detection using multiple deep learning models for global and local representations of waveformscited by 1
  25. 2024A Physics-Embedded Dual-Learning Imaging Framework for Electrical Impedance Tomographycited by 1
  26. 2025FPGA-based Acceleration for Convolutional Neural Networks: A Comprehensive Reviewcited by 1
  27. 2022CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detectioncited by 0
  28. 2023Global Relation Modeling and Refinement for Bottom-Up Human Pose Estimationcited by 0
  29. 2024Multi-Object Tracking by Hierarchical Visual Representationscited by 0
  30. 2024AdaContour: Adaptive Contour Descriptor with Hierarchical Representationcited by 0
  31. 2024Non-parametric Contextual Relationship Learning for Semantic Video Object Segmentationcited by 0
  32. 2024Context Propagation from Proposals for Semantic Video Object Segmentationcited by 0
  33. 2024DFMSD: Dual Feature Masking Stage-wise Knowledge Distillation for Object Detectioncited by 0
  34. 2025Ice Hockey Puck Localization Using Contextual Cuescited by 0
  35. 2025Evaluating Open-Source Vision Language Models for Facial Emotion Recognition against Traditional Deep Learning Modelscited by 0