Paper list of monocular 3D human pose and shape estimation

Table of Contents

• Single-view recovery
• 2D pose to 3D pose
• Video
• Multi-view recovery
• Multi-person
• Detailed geometry
• Self-supervise/ weak supervise
• Interaction with scene
• Total capture
• Future prediction
• Other input
• Others
• 3D Hands

Single-view recovery

• [CVPR2021] Frank Yu et al., PCLs: Geometry-aware Neural Reconstruction of 3D Pose with Perspective Crop Layers

• [ECCV2020]，I2L-MeshNet: Image-to-Lixel Prediction Network for Accurate 3D Human Pose and Mesh Estimation from a Single RGB Image

• [CVPR2020]，3D Human Mesh Regression with Dense Correspondence

• [ICCV2019]，Georgios Pavlakos et al，TexturePose: Supervising Human Mesh Estimation with Texture Consistency

• [ICCV2019], Nikos Kolotouros et al., Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the Loop

• [ICCV2019], Saurabh Sharma et al., Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking

• [ICCV2019], Kun Zhou et al., HEMlets Pose: Learning Part-Centric Heatmap Triplets for Accurate 3D Human Pose Estimation

• [CVPR2019], Long Zhao et al., Semantic Graph Convolutional Networks for 3D Human Pose Regression

• [CVPR2019], Chen Li et al., Generating Multiple Hypotheses for 3D Human Pose Estimation With Mixture Density Network

• [CVPR2019], Riza Alp Guler et al.， HoloPose: Holistic 3D Human Reconstruction In-The-Wild

• [CVPR2019], Xipeng Chen et al.， Weakly-Supervised Discovery of Geometry-Aware Representation for 3D Human Pose Estimation

• [CVPR2019], Ikhsanul Habibie et al.， In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations

2D pose to 3D pose

• [CVPR2021] Xiaoxuan Ma et al., Context Modeling in 3D Human Pose Estimation: A Unified Perspective

• [CVPR2021] Tianhan Xu et al., Graph Stacked Hourglass Networks for 3D Human Pose Estimation

• [ICCV2019], Hai Ci et al., Optimizing Network Structure for 3D Human Pose Estimation

• [CVPR2019], Dario Pavllo et al., 3D Human Pose Estimation in Video With Temporal Convolutions and Semi-Supervised Training

Video

• [CVPR2021] Hongsuk Choi et al., Beyond Static Features for Temporally Consistent 3D Human Pose and Shape from a Video

• [CVPR2021] Ye Yuan et al., SimPoE: Simulated Character Control for 3D Human Pose Estimation

• [CVPR2020] Muhammed Kocabas et al., VIBE: Video Inference for Human Body Pose and Shape Estimation

• [CVPR2019] Angjoo Kanazawa et al., Learning 3D Human Dynamics from Video

• [ICCV2019], Jason Y. Zhang et al., Predicting 3D Human Dynamics from Video

• [ICCV2019], Yu Sun et al., Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation

• [CVPR2019], Anurag Arnab et al., Exploiting temporal context for 3D human pose estimation in the wild

Multi-view recovery

• [ECCV2020] Junting Dong et al., Motion Capture from Internet Videos
• [ICCV2019], Nitin Saini et al., Markerless Outdoor Human Motion Capture Using Multiple Autonomous Micro Aerial Vehicles
• [ICCV2019], Haibo Qiu et al., Cross View Fusion for 3D Human Pose Estimation
• [ICCV2019], Junbang Liang et al., Shape-Aware Human Pose and Shape Reconstruction Using Multi-View Images
• [ICCV2019], Karim Iskakov et al., Learnable Triangulation of Human Pose
• [CVPR2020], Yuxiang Zhang et al., 4D Association Graph for Realtime Multi-Person Motion Capture Using Multiple Video Cameras
• [CVPR2019], Junting Dong et al., Fast and Robust Multi-Person 3D Pose Estimation From Multiple Views

Multi-person

• [CVPR2021] Yu Cheng et al., Monocular 3D Multi-Person Pose Estimation by Integrating Top-Down and Bottom-Up Networks
• [AAAI2021] Yu Cheng et al., Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos
• [ECCV2020] Jianan Zhen et al., SMAP: Single-Shot Multi-Person Absolute 3D Pose Estimation
• [ECCV2020] Jogendra Nath Kundu et al., Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation
• [ECCV2020] Jiefeng Li et al., HMOR: Hierarchical Multi-Person Ordinal Relations for Monocular Multi-Person 3D Pose Estimation
• [ECCV2020] Jiahao Lin et al., HDNet: Human Depth Estimation for Multi-Person Camera-Space Localization
• [CVPR2020] Mihai Fieraru et al., Three-dimensional Reconstruction of Human Interactions
• [(SIGGRAPH) 2020] Dushyant Mehta et al., XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
• [CVPR2020] Matteo Fabbri et al., Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation
• [CVPR2020] Abdallah Benzine et al., PandaNet : Anchor-Based Single-Shot Multi-Person 3D Pose Estimation
• [CVPR2020] Wen Jiang et al., Coherent Reconstruction of Multiple Humans From a Single Image
• [ICCV 2019] Gyeongsik Moon et al., Camera Distance-aware Top-down Approach for 3D Multi-person Pose Estimation from a Single RGB Image

Other input

• [CVPR2021] Vladimir Guzov et al., Human POSEitioning System (HPS): 3D Human Pose Estimation and Self- localization in Large Scenes from Body-Mounted Sensors

• [CVPR2021] Qi Fang et al., Reconstructing 3D Human Pose by Watching Humans in the Mirror

• [CVPR2021] Yiyue Luo et al., Intelligent Carpet: Inferring 3D Human Pose from Tactile Signals

• [ICCV2019], Haiyong Jiang et al., Skeleton-Aware 3D Human Shape Reconstruction From Point Clouds

• [ICCV2019], Denis Tome et al., xR-EgoPose: Egocentric 3D Human Pose from an HMD Camera

Detailed geometry

• [CVPR2021], Yan Zhang et al., We are More than Our Joints: Predicting how 3D Bodies Move

• [CVPR2021], Jiefeng Li et al., HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimation

• [ECCV2020] CLOTH3D: Clothed 3D Humans

• [ECCV2020] Combining Implicit Function Learning and Parametric Models for 3D Human Reconstruction

• [ECCV2020] Luyang Zhu et al., Reconstructing NBA Players

• [CVPR2020] Shunsuke Saito et al., PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

• [CVPR2020] Marc Habermann et al., DeepCap: Monocular Human Performance Capture Using Weak Supervision

• [CVPR2020] Shunsuke Saito et al., PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization

• [CVPR2020] Feitong Tan et al., Self-Supervised Human Depth Estimation from Monocular Videos

• [CVPR2020] Zeng Huang et al., ARCH: Animatable Reconstruction of Clothed Humans

• [CVPR2020] Hayato Onizuka et al., TetraTSDF: 3D human reconstruction from a single image with a tetrahedral outer shell

• [CVPR2020] Yong-Lu Li et al., Detailed 2D-3D Joint Representation for Human-Object Interaction

• [ICCV2019] Shunsuke Saito et al., PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitization

• [ICCV2019], Zerong Zheng et al., DeepHuman: 3D Human Reconstruction From a Single Image

• [ICCV2019], Albert Pumarola et al., 3DPeople: Modeling the Geometry of Dressed Humans

• [ICCV19] Thiemo Alldieck et al., Tex2Shape: Detailed Full Human Body Geometry From a Single Image

• [ICCV19] Sicong Tang et al., A Neural Network for Detailed Human Depth Estimation From a Single Image

• [CVPR19 Oral] Ryota Natsume et al., SiCloPe: Silhouette-Based Clothed People

• [CVPR19 Oral] Nikos Kolotouros et al.，Convolutional Mesh Regression for Single-Image Human Shape Reconstruction

• [CVPR19 Oral] Hao Zhu et al., Detailed Human Shape Estimation from a Single Image by Hierarchical mesh deformation

• [CVPR2019], Thiemo Alldieck et al., Learning to Reconstruct People in Clothing from a Single RGB Camera

• [CVPR19] Thiemo Alldieck et al., Learning to Reconstruct People in Clothing from a Single RGB Camera

• [CVPR19] Tao Yu et al., SimulCap: Single-View Human Performance Capture with Cloth Simulation

• [TOG 2019] Marc Habermann et al., LiveCap: Real-Time Human Performance Capture From Monocular Video

• [ICCV2019] Valentin Gabeur et al., Moulding Humans: Non-parametric 3D Human Shape Estimation from Single Images

Self-supervise/ weak supervise

• [CVPR2021] Bastian Wandt et al., CanonPose: Self-Supervised Monocular 3D Human Pose Estimation in the Wild

• [CVPR2019] Muhammed Kocabas et al., Self-Supervised Learning of 3D Human Pose using Multi-view Geometry

• [CVPR2019], Bastian Wandt et al., RepNet: Weakly Supervised Training of an Adversarial Reprojection Network for 3D Human Pose Estimation

Interaction with scene

• [CVPR 2020] Yong-Lu Li et al., Detailed 2D-3D Joint Representation for Human-Object Interaction

• [ICCV 2019] Mohamed Hassan et al., Resolving 3D Human Pose Ambiguities with 3D Scene Constraints

• [ICCV 2019] Yixin Chen et al., Holistic++ Scene Understanding: Single-view 3D Holistic Scene Parsing and Human Pose Estimation with Human-Object Interaction and Physical Commonsense

Occlusion

• [CVPR2020] Object-Occluded Human Shape and Pose Estimation from a Single Color Image
• [ICCV2019] Yu Cheng et al., Occlusion-Aware Networks for 3D Human Pose Estimation in Video

Total capture

• [CVPR2019] Donglai Xiang et al., Monocular Total Capture: Posing Face, Body and Hands in the Wild
• [CVPR2019] Georgios Pavlakos et al., Expressive Body Capture: 3D Hands, Face, and Body from a Single Image

Future prediction

• [ECCV2020] Long-term Human Motion Prediction with Scene Context
• [ICCV2019] Zhi Li et al., On Boosting Single-Frame 3D Human Pose Estimation via Monocular Videos
• [ICCV2019] A. Hernandez Ruiz et al., Human Motion Prediction via Spatio-Temporal Inpainting
• [ICCV2019] Emre Aksan et al., Structured Prediction Helps 3D Human Motion Modelling
• [ICCV2019] Wei Mao et al., Learning Trajectory Dependencies for Human Motion Prediction
• [CVPR2019] Zhenguang Liu et al., Towards Natural and Accurate Future Motion Prediction of Humans and Animals
• [CVPR2019] Anand Gopalakrishnan et al.， A Neural Temporal Model for Human Motion Prediction

Others

• [CVPR2021] Kehong Gong et al., PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation

• [ICCV19] Yu Rong et al., Delving Deep Into Hybrid Annotations for 3D Human Recovery in the Wild

• [CVPR19] Chung-Yi Weng et al., Photo Wake-Up: 3D Character Animation from a Single Phot

• [CVPR2019] Rohit Pandey et al. Volumetric Capture of Humans with a Single RGBD Camera via Semi-Parametric Learning

3D-Hands

• [CVPR2020]，Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild