Resources: • https://towardsdatascience.com/human-pose-estimation-simplified-6cfd88542ab3 • https://nanonets.com/blog/human-pose-estimation-2d-guide • https://heartbeat.fritz.ai/a-2019-guide-to-human-pose-estimation-c10b79b64b73 • Coco tools for python 3 ○ https://github.com/philferriere/cocoapi Papers: • Survey: https://arxiv.org/pdf/2006.01423.pdf • DeepPose: https://arxiv.org/abs/1312.4659 • Heatmap prediction ○ https://arxiv.org/pdf/1406.2984.pdf ○ https://arxiv.org/pdf/1411.4280.pdf • Convolutional Pose Machine ○ https://arxiv.org/pdf/1602.00134.pdf ○ https://arxiv.org/pdf/1906.04104.pdf ○ Multi-person § https://arxiv.org/pdf/1611.08050.pdf § https://arxiv.org/pdf/1911.10529v1.pdf § https://arxiv.org/pdf/1807.04067.pdf § OpenPose - https://arxiv.org/pdf/1812.08008.pdf § https://arxiv.org/pdf/1909.13423.pdf § https://arxiv.org/pdf/1908.05593.pdf § https://arxiv.org/pdf/1903.06593v2.pdf § https://arxiv.org/pdf/1803.08225.pdf § https://arxiv.org/pdf/1812.00324.pdf § https://arxiv.org/pdf/1612.00137.pdf § https://arxiv.org/pdf/1911.07451v2.pdf • Stacked Hourglass - https://arxiv.org/pdf/1603.06937.pdf • Simple baseline - https://arxiv.org/pdf/1804.06208.pdf • High resolution representations learning ○ https://arxiv.org/pdf/1902.09212.pdf ○ https://arxiv.org/pdf/1908.07919v2.pdf ○ Multi-person § HigherHRNet - https://arxiv.org/pdf/1908.10357v3.pdf • Multi-person-single stage - https://arxiv.org/pdf/1909.13423v1.pdf • 3d ○ https://arxiv.org/pdf/1901.03798v2.pdf ○ https://arxiv.org/pdf/2003.02953.pdf ○ https://arxiv.org/pdf/2001.05097.pdf ○ https://arxiv.org/pdf/1907.00837v2.pdf ○ https://arxiv.org/pdf/1907.11346v2.pdf ○ https://arxiv.org/pdf/1705.03098v2.pdf ○ IMU- https://arxiv.org/pdf/1912.04071.pdf • Video ○ https://arxiv.org/pdf/1712.09184v2.pdf • Synthetic data - https://arxiv.org/pdf/1701.01370v3.pdf • Multi-Stage best - https://arxiv.org/pdf/1901.00148v4.pdf • Multi-Camera - https://arxiv.org/pdf/1905.05754v1.pdf • CPN - https://arxiv.org/pdf/1711.07319v2.pdf • Ellipbody - https://arxiv.org/pdf/2003.10873.pdf • Efficient - https://arxiv.org/pdf/2004.12186.pdf • Mesh - https://arxiv.org/pdf/1808.05942v1.pdf ○ https://arxiv.org/pdf/1905.03244v1.pdf • Refinement Stage - https://arxiv.org/pdf/1812.03595v3.pdf • https://arxiv.org/pdf/1708.01101v1.pdf • Fast ○ https://arxiv.org/pdf/1811.05419v2.pdf • Pose Flow - https://arxiv.org/pdf/1802.00977.pdf • LSTM Pose Machines - https://arxiv.org/pdf/1712.06316v4.pdf • https://arxiv.org/pdf/1908.09999v1.pdf • https://arxiv.org/pdf/2001.08095v1.pdf • https://arxiv.org/pdf/2002.11098v1.pdf • https://arxiv.org/pdf/1910.06278v1.pdf • https://arxiv.org/pdf/1711.07399v3.pdf • IEF - https://arxiv.org/pdf/1507.06550.pdf • http://openaccess.thecvf.com/content_ECCV_2018/papers/Sekii_Pose_Proposal_Networks_ECCV_2018_paper.pdf
Dataset • PoseTrack