mlsanityData to 14 Oct 2026

BAPose: Bottom-Up Pose Estimation with Disentangled Waterfall Representations

arXiv 2112.10716 ↗First posted 20 Dec 2021cs.CVcited by 3

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Abstract (arXiv)

We propose BAPose, a novel bottom-up approach that achieves state-of-the-art results for multi-person pose estimation. Our end-to-end trainable framework leverages a disentangled multi-scale waterfall architecture and incorporates adaptive convolutions to infer keypoints more precisely in crowded scenes with occlusions. The multi-scale representations, obtained by the disentangled waterfall module in BAPose, leverage the efficiency of progressive filtering in the cascade architecture, while maintaining multi-scale fields-of-view comparable to spatial pyramid configurations. Our results on the challenging COCO and CrowdPose datasets demonstrate that BAPose is an efficient and robust framework for multi-person pose estimation, achieving significant improvements on state-of-the-art accuracy.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 41 of its 46 references that are in the map. First posted on arXiv 20 Dec 2021.

Builds on

41 of 46 references.

References · 41

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  2. 2017Mask R-CNNcited by 7,277
  3. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
  4. 2016DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFscited by 3,241
  5. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,223
  6. 2018YOLOv3: An Incremental Improvementcited by 2,659
  7. 2015Spatial Transformer Networkscited by 1,429
  8. 2019Deep High-Resolution Representation Learning for Human Pose Estimationcited by 1,339
  9. 2019Objects as Pointscited by 1,175
  10. 2016Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,064
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  12. 2018DensePose: Dense Human Pose Estimation In The Wildcited by 575
29 more
  1. 2016RMPE: Regional Multi-person Pose Estimationcited by 340
  2. 2016Convolutional Pose Machinescited by 325
  3. 2013DeepPose: Human Pose Estimation via Deep Neural Networkscited by 305
  4. 2019HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimationcited by 247
  5. 2018CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmarkcited by 214
  6. 2016Associative Embedding: End-to-End Learning for Joint Detection and Groupingcited by 212
  7. 2019Distribution-Aware Coordinate Representation for Human Pose Estimationcited by 165
  8. 2018PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Modelcited by 133
  9. 2019PifPaf: Composite Fields for Human Pose Estimationcited by 120
  10. 2015DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimationcited by 117
  11. 2021Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regressioncited by 112
  12. 2021TokenPose: Learning Keypoint Tokens for Human Pose Estimationcited by 107
  13. 2016DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Modelcited by 96
  14. 2019Single-Stage Multi-Person Pose Machinescited by 95
  15. 2017Multi-Context Attention for Human Pose Estimationcited by 66
  16. 2019Rethinking on Multi-Stage Networks for Human Pose Estimationcited by 58
  17. 2020Point-Set Anchors for Object Detection, Instance Segmentation and Pose Estimationcited by 57
  18. 2020Differentiable Hierarchical Graph Grouping for Multi-Person Pose Estimationcited by 52
  19. 2020UniPose: Unified Human Pose Estimation in Single Images and Videoscited by 49
  20. 2017MonoCap: Monocular Human Motion Capture using a CNN Coupled with a Geometric Priorcited by 36
  21. 2021Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimationcited by 30
  22. 2019Mixture Dense Regression for Object Detection and Human Pose Estimationcited by 29
  23. 2016Recurrent Human Pose Estimationcited by 27
  24. 2019Human Pose Estimation with Spatial Contextual Informationcited by 21
  25. 20183D Human Pose Estimation with 2D Marginal Heatmapscited by 20
  26. 2019LightTrack: A Generic Framework for Online Top-Down Human Pose Trackingcited by 16
  27. 2019Cascade Feature Aggregation for Human Pose Estimationcited by 8
  28. 2021OmniPose: A Multi-Scale Framework for Multi-Person Pose Estimationcited by 6
  29. 2019Waterfall Atrous Spatial Pooling Architecture for Efficient Semantic Segmentationcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.

3 papers.

  1. 2023Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguitycited by 13
  2. 2024Waterfall Transformer for Multi-person Pose Estimationcited by 1
  3. 2026FSMC-Pose: Frequency and Spatial Fusion with Multiscale Self-calibration for Cattle Mounting Pose Estimationcited by 0