mlsanityData to 7 Oct 2026

GatedUniPose: A Novel Approach for Pose Estimation Combining UniRepLKNet and Gated Convolution

arXiv 2409.07752 ↗First posted 12 Sep 2024cs.CVcited by 1

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Abstract (arXiv)

Pose estimation is a crucial task in computer vision, with wide applications in autonomous driving, human motion capture, and virtual reality. However, existing methods still face challenges in achieving high accuracy, particularly in complex scenes. This paper proposes a novel pose estimation method, GatedUniPose, which combines UniRepLKNet and Gated Convolution and introduces the GLACE module for embedding. Additionally, we enhance the feature map concatenation method in the head layer by using DySample upsampling. Compared to existing methods, GatedUniPose excels in handling complex scenes and occlusion challenges. Experimental results on the COCO, MPII, and CrowdPose datasets demonstrate that GatedUniPose achieves significant performance improvements with a relatively small number of parameters, yielding better or comparable results to models with similar or larger parameter sizes.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 39 of its 50 references that are in the map. First posted on arXiv 12 Sep 2024.

Builds on

39 of 50 references.

References · 39

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2021Swin Transformer: Hierarchical Vision Transformer using Shifted Windowscited by 12,082
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  11. 2022ViTPose: Simple Vision Transformer Baselines for Human Pose Estimationcited by 450
  12. 2016RMPE: Regional Multi-person Pose Estimationcited by 340
27 more
  1. 2019HigherHRNet: Scale-Aware Representation Learning for Bottom-Up Human Pose Estimationcited by 247
  2. 2018CrowdPose: Efficient Crowded Scenes Pose Estimation and A New Benchmarkcited by 214
  3. 2016Associative Embedding: End-to-End Learning for Joint Detection and Groupingcited by 211
  4. 2019Distribution-Aware Coordinate Representation for Human Pose Estimationcited by 165
  5. 2021HRFormer: High-Resolution Transformer for Dense Predictioncited by 149
  6. 2020TransPose: Keypoint Localization via Transformercited by 126
  7. 2021Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regressioncited by 112
  8. 2018Pose2Seg: Detection Free Human Instance Segmentationcited by 107
  9. 2021TokenPose: Learning Keypoint Tokens for Human Pose Estimationcited by 106
  10. 2021Pose Recognition with Cascade Transformerscited by 99
  11. 2019The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimationcited by 79
  12. 2023UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognitioncited by 64
  13. 2017AlignedReID: Surpassing Human-Level Performance in Person Re-Identificationcited by 61
  14. 2023UniHCP: A Unified Model for Human-Centric Perceptionscited by 59
  15. 2023Learning to Upsample by Learning to Samplecited by 57
  16. 2021OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Associationcited by 55
  17. 2023Human Pose as Compositional Tokenscited by 45
  18. 2019Deep learning tools for the measurement of animal behavior in neurosciencecited by 44
  19. 2021TFPose: Direct Human Pose Estimation with Transformerscited by 42
  20. 2021Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimationcited by 30
  21. 2016ArtTrack: Articulated Multi-person Tracking in the Wildcited by 27
  22. 2020Peeking into occluded joints: A novel framework for crowd pose estimationcited by 25
  23. 2021Rethinking Keypoint Representations: Modeling Keypoints and Poses as Objects for Multi-Person Human Pose Estimationcited by 20
  24. 2021The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimationcited by 18
  25. 2015Bottom-Up and Top-Down Reasoning with Hierarchical Rectified Gaussianscited by 14
  26. 2023Rethinking pose estimation in crowds: overcoming the detection information-bottleneck and ambiguitycited by 13
  27. 2022Self-Constrained Inference Optimization on Structural Groups for Human Pose Estimationcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026A Geometry-Driven, Framework-Agnostic Optimization for Object Pose Estimationcited by 0