└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Human Pose Estimation from RGB Camera - The repo 2 | In recent years, tremendous amount of progress is being made in the field of Human Pose Estimation from RGB Camera, which is an interdisciplinary field that fuses computer vision, deep/machine learning and anatomy. This repo is for my study notes and will be used as a place for triaging new research papers. 3 | 4 | ## Get Involved 5 | To make it a collaborative project, you may add content through pull requests or open an issue to let me know. 6 | 7 | ## Table of Contents 8 | 9 | I'll use the following icons and dimensions to differentiate the approaches: 10 | 11 | - Time Dimension 12 | - :camera: Single-Shot 13 | - :movie_camera: Video/Real-Time 14 | - Number of People 15 | - :one: Single-Person 16 | - :1234: Multi-Person 17 | - Spatial Dimensions 18 | - [2D Models](#2d_models) 19 | - [3D Models](#3d_models) 20 | 21 | ## Projects and papers 22 | 23 | 24 | 25 | ### 2D Models 26 | :movie_camera::1234: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields (2017) [[Project page]](https://github.com/ZheC/Realtime_Multi-Person_Pose_Estimation)[[Paper]](https://arxiv.org/pdf/1611.08050.pdf) 27 | 28 | :camera::one: Stacked Hourglass Networks for Human Pose Estimation (2016) [[Paper]](https://arxiv.org/pdf/1603.06937.pdf) 29 | 30 | :camera::one: Convolutional Pose Machines (2016) [[Paper]](https://arxiv.org/pdf/1602.00134.pdf) 31 | 32 | :camera::one: Adversarial PoseNet: A Structure-aware Convolutional Network for Human Pose Estimation (2017) [[Paper]](https://arxiv.org/pdf/1705.00389.pdf) 33 | 34 | :camera::one: Knowledge-Guided Deep Fractal Neural Networks for Human Pose Estimation (2017) [[Project page]](https://github.com/Guanghan/GNet-pose) [[Paper]](https://arxiv.org/pdf/1705.02407.pdf) 35 | 36 | 37 | 38 | ### 3D Models 39 | :camera::one: A simple yet effective baseline for 3d human pose estimation (2017) [[Project page]](https://github.com/una-dinosauria/3d-pose-baseline)[[Paper]](https://arxiv.org/pdf/1705.03098.pdf) 40 | 41 | :movie_camera::one: VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera (2017) [[Project page]](http://gvv.mpi-inf.mpg.de/projects/VNect/)[[Paper]](http://gvv.mpi-inf.mpg.de/projects/VNect/content/VNect_SIGGRAPH2017.pdf) 42 | 43 | :camera::1234: Single-Shot Multi-Person 3D Body Pose Estimation From Monocular RGB Input (2018) [[Paper]](https://arxiv.org/pdf/1712.03453.pdf) 44 | 45 | :camera::one: Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision (2017) [[Project page]](http://gvv.mpi-inf.mpg.de/3dhp-dataset/)[[Paper]](https://arxiv.org/pdf/1611.09813.pdf) 46 | 47 | :camera::1234: DensePose: Dense Human Pose Estimation In The Wild (2018) [[Project page]](http://densepose.org)[[Paper]](https://arxiv.org/pdf/1802.00434.pdf) 48 | 49 | :movie_camera::one: End-to-end Recovery of Human Shape and Pose (2017) [[Project page]](https://github.com/akanazawa/hmr)[[Paper]](https://arxiv.org/pdf/1712.06584.pdf) 50 | 51 | :movie_camera::1234: LCR-Net++: Multi-person 2D and 3D Pose Detection in Natural Images (2018) [[Project page]](https://thoth.inrialpes.fr/src/LCR-Net/)[[Paper]](https://arxiv.org/pdf/1803.00455.pdf) 52 | 53 | :movie_camera::one: Spatio-temporal Matching for Human Pose Estimation (2014) [[Project page]](http://www.f-zhou.com/hpe.html)[[Paper]](http://www.f-zhou.com/hpe/2014_ECCV_STM.pdf) 54 | 55 | :movie_camera::one: Sparseness Meets Deepness: 3D Human Pose Estimation from Monocular Video (2016) [[Paper]](https://arxiv.org/pdf/1511.09439.pdf) 56 | 57 | :camera::one: Learning to Fuse 2D and 3D Image Cues for Monocular Body Pose Estimation (2017) [[Paper]](https://arxiv.org/pdf/1611.05708.pdf) 58 | 59 | :camera::one: Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image (2016) [[Paper]](https://arxiv.org/pdf/1607.08128.pdf) 60 | 61 | :camera::one: MoCap-guided Data Augmentation for 3D Pose Estimation in the Wild (2016) [[Paper]](https://arxiv.org/pdf/1607.02046.pdf) 62 | 63 | :camera::one: Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image (2017) [[Paper]](https://arxiv.org/pdf/1701.00295.pdf) 64 | 65 | :movie_camera::one: MonoPerfCap: Human Performance Capture from Monocular Video (2018) [[Project page]](http://gvv.mpi-inf.mpg.de/projects/wxu/MonoPerfCap/) [[Paper]](http://gvv.mpi-inf.mpg.de/projects/wxu/MonoPerfCap/content/monoperfcap.pdf) 66 | 67 | :camera::one: Unsupervised Adversarial Learning of 3D Human Pose from 2D Joint Locations (2018) [[Project page]](https://nico-opendata.jp/en/casestudy/3dpose_gan/index.html) [[Paper]](https://arxiv.org/pdf/1803.08244.pdf) 68 | 69 | :camera::one: 3D Human Pose Estimation in the Wild by Adversarial Learning (2018) [[Paper]](https://arxiv.org/pdf/1803.09722.pdf) 70 | 71 | :camera::1234: Deep Human Pose Estimation Using Cascade of Multiple Neural Networks (2018) [[Paper]](https://ieeexplore.ieee.org/document/8432121/) 72 | 73 | :movie_camera::one: Deep 3D Human Pose Estimation Under Partial Body Presence (2018) [[Paper]](https://ieeexplore.ieee.org/document/8451031) 74 | 75 | :movie_camera::one: 3D Ego-Pose Estimation via Imitation Learning (2018) [[Paper]](http://openaccess.thecvf.com/content_ECCV_2018/papers/Ye_Yuan_3D_Ego-Pose_Estimation_ECCV_2018_paper.pdf) 76 | 77 | :camera::one: Neural Body Fitting: Unifying Deep Learning and Model-Based Human Pose and Shape Estimation (2018) [[Paper]](https://arxiv.org/pdf/1808.05942.pdf) 78 | --------------------------------------------------------------------------------