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→Pose Estimation Related Models
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| 4 || MoveNet || Google Research || Detecting 17 critical key points of the human body || [https://github.com/tensorflow/tfjs-models/tree/master/posenet MoveNet GitHub] || Apache 2.0
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| 5 || PoseNet || Google Research || Detecting different body parts, providing comprehensive skeletal information || [https://github.com/tensorflow/tfjs-models/tree/master/posenet PoseNet GitHub] || Apache 2.0
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| 6 || DCPose || Deep Dual Consecutive Network || Detecting human pose from multiple frames, addressing motion blur and occlusions || [https://github.com/DeepDualConsecutivePose/dcpose DCPose GitHub] || MIT
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| 7 || DensePose || Facebook AI Research || Mapping human-based pixels from an RGB image to the 3D surface of a human body || [https://github.com/facebookresearch/DensePose DensePose GitHub] || Apache 2.0
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| 8 || HigherHRNet || HRNet || Addressing scaling differences in pose prediction, especially for shorter people || [https://github.com/HRNet/HigherHRNet HigherHRNet GitHub] || MIT
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| 9 || Lightweight OpenPose || Daniil-Osokin || Real-time inference with minimal accuracy drop, detecting human poses through key points || [https://github.com/Daniil-Osokin/lightweight-human-pose-estimation Lightweight OpenPose GitHub] || MIT
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| 10 || AlphaPose || MVIG-SJTU || Detecting multiple individuals in various scenes, achieving high mAP on COCO and MPII datasets || [https://github.com/MVIG-SJTU/AlphaPose AlphaPose GitHub] || MIT
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