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Associative Embedding: End-to-End Learning for Joint Detection and Grouping

arXiv 1611.05424 ↗First posted 16 Nov 2016cs.CVcited by 211

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Abstract (arXiv)

We introduce associative embedding, a novel method for supervising convolutional neural networks for the task of detection and grouping. A number of computer vision problems can be framed in this manner including multi-person pose estimation, instance segmentation, and multi-object tracking. Usually the grouping of detections is achieved with multi-stage pipelines, instead we propose an approach that teaches a network to simultaneously output detections and group assignments. This technique can be easily integrated into any state-of-the-art network architecture that produces pixel-wise predictions. We show how to apply this method to both multi-person pose estimation and instance segmentation and report state-of-the-art performance for multi-person pose on the MPII and MS-COCO datasets.

Key facts. Cited by 211 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Nov 2016.

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Citing papers per year: 2021: 80; 2022: 51; 2023: 38; 2024: 22; 2025: 12; 2026: 8.

211 papers.

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  1. 2023Effective Whole-body Pose Estimation with Two-stages Distillationcited by 307
  2. 2021Revisiting Skeleton-based Action Recognitioncited by 256
  3. 2021K-Net: Towards Unified Image Segmentationcited by 211
  4. 2022AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking in Real-Timecited by 199
  5. 2023RTMPose: Real-Time Multi-Person Pose Estimation based on MMPosecited by 170
  6. 2021Human Pose Regression with Residual Log-likelihood Estimationcited by 131
  7. 2021AP-10K: A Benchmark for Animal Pose Estimation in the Wildcited by 123
  8. 2021Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regressioncited by 112
  9. 2021TokenPose: Learning Keypoint Tokens for Human Pose Estimationcited by 106
  10. 2021Recent advances and clinical applications of deep learning in medical image analysiscited by 104
  11. 2022FreeSOLO: Learning to Segment Objects without Annotationscited by 102
  12. 2021Pose Recognition with Cascade Transformerscited by 99
38 more
  1. 2022Not All Tokens Are Equal: Human-centric Visual Analysis via Token Clustering Transformercited by 99
  2. 2021Graph Stacked Hourglass Networks for 3D Human Pose Estimationcited by 94
  3. 2021SG-Net: Spatial Granularity Network for One-Stage Video Instance Segmentationcited by 87
  4. 2021Video Instance Segmentation with a Propose-Reduce Paradigmcited by 74
  5. 2021SOLQ: Segmenting Objects by Learning Queriescited by 68
  6. 2021SimCC: a Simple Coordinate Classification Perspective for Human Pose Estimationcited by 68
  7. 2022YOLO-Pose: Enhancing YOLO for Multi Person Pose Estimation Using Object Keypoint Similarity Losscited by 66
  8. 2021Focus on Local: Detecting Lane Marker from Bottom Up via Key Pointcited by 65
  9. 2022ViTPose++: Vision Transformer for Generic Body Pose Estimationcited by 65
  10. 2021Learning to Estimate Robust 3D Human Mesh from In-the-Wild Crowded Scenescited by 64
  11. 2023Contrastive Lift: 3D Object Instance Segmentation by Slow-Fast Contrastive Fusioncited by 62
  12. 2021Semantics for Robotic Mapping, Perception and Interaction: A Surveycited by 56
  13. 2021OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Associationcited by 55
  14. 2021Recent Advances in Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspectivecited by 49
  15. 2022DiffusionInst: Diffusion Model for Instance Segmentationcited by 49
  16. 2023Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimationcited by 48
  17. 2023Human Pose as Compositional Tokenscited by 45
  18. 2021VolumeFusion: Deep Depth Fusion for 3D Scene Reconstructioncited by 44
  19. 2021TFPose: Direct Human Pose Estimation with Transformerscited by 42
  20. 2021Spatial Feature Calibration and Temporal Fusion for Effective One-stage Video Instance Segmentationcited by 42
  21. 2021When Human Pose Estimation Meets Robustness: Adversarial Algorithms and Benchmarkscited by 41
  22. 2021VoxelTrack: Multi-Person 3D Human Pose Estimation and Tracking in the Wildcited by 39
  23. 2021Learning Dynamics via Graph Neural Networks for Human Pose Estimation and Trackingcited by 37
  24. 2022AISFormer: Amodal Instance Segmentation with Transformercited by 35
  25. 2021FCPose: Fully Convolutional Multi-Person Pose Estimation with Dynamic Instance-Aware Convolutionscited by 34
  26. 2021PlaneTR: Structure-Guided Transformers for 3D Plane Recoverycited by 33
  27. 2022Look Before You Match: Instance Understanding Matters in Video Object Segmentationcited by 33
  28. 2021SOLO: A Simple Framework for Instance Segmentationcited by 32
  29. 2021Differentiable Multi-Granularity Human Representation Learning for Instance-Aware Human Semantic Parsingcited by 31
  30. 2022Action Quality Assessment with Temporal Parsing Transformercited by 31
  31. 2021Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimationcited by 30
  32. 2021End-to-End Trainable Multi-Instance Pose Estimation with Transformerscited by 30
  33. 2023Group Pose: A Simple Baseline for End-to-End Multi-person Pose Estimationcited by 26
  34. 2022CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal Posecited by 25
  35. 2022JRDB-Pose: A Large-scale Dataset for Multi-Person Pose Estimation and Trackingcited by 25
  36. 2021Shape-aware Multi-Person Pose Estimation from Multi-View Imagescited by 24
  37. 2022ZoomNAS: Searching for Whole-body Human Pose Estimation in the Wildcited by 23
  38. 2021PandaNet : Anchor-Based Single-Shot Multi-Person 3D Pose Estimationcited by 22

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