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Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision [article]

Dushyant Mehta, Helge Rhodin, Dan Casas, Pascal Fua, Oleksandr Sotnychenko, Weipeng Xu, Christian Theobalt
2017 arXiv   pre-print
All in all, we argue that the use of transfer learning of representations in tandem with algorithmic and data contributions is crucial for general 3D body pose estimation.  ...  Using only the existing 3D pose data and 2D pose data, we show state-of-the-art performance on established benchmarks through transfer of learned features, while also generalizing to in-the-wild scenes  ...  Supplemental Document: Monocular 3D Human Pose Estimation In The Wild Using Improved CNN Supervision This document accompanies the main paper, and the supplemental video.  ... 
arXiv:1611.09813v5 fatcat:uka37jvzbzefzow7td73phrfly

Deep Learning Methods for 3D Human Pose Estimation under Different Supervision Paradigms: A Survey

Dejun Zhang, Yiqi Wu, Mingyue Guo, Yilin Chen
2021 Electronics  
The literature is reviewed, along with the general pipeline of 3D human pose estimation, which consists of human body modeling, learning-based pose estimation, and regularization for refinement.  ...  Based on this literature survey, it can be concluded that each branch of 3D human pose estimation starts with fully-supervised methods, and there is still much room for multi-person pose estimation based  ...  [21] is a recently published a survey of deep learning-based monocular human pose estimation, which contains both 2D and 3D human pose estimation.  ... 
doi:10.3390/electronics10182267 fatcat:ajnizu776ncpto3jvyh3zye2si

Leaving Flatland: Advances in 3D behavioral measurement [article]

Jesse D. Marshall, Tianqing Li, Joshua H. Wu, Timothy W. Dunn
2021 arXiv   pre-print
Continued advances at the intersection of deep learning and computer vision will facilitate 3D tracking across more anatomical features, with less training data, in additional species, and within more  ...  Existing 3D measurement techniques draw on specialized hardware, such as motion capture or depth cameras, as well as deep multi-view and monocular computer vision.  ...  Transfer learning refers to when a network pretrained on one dataset for a specific task, for instance human 3D pose estimation, performs learns better on a different task, such as rat 3D pose estimation  ... 
arXiv:2112.01987v1 fatcat:z5dqj47s3fbt3d4t75bnsp2l6q

Monocular Depth Estimation using Transfer learning-An Overview

K. Swaraja, V. Akshitha, K. Pranav, B. Vyshnavi, V. Sai Akhil, K. Meenakshi, Padmavathi Kora, Himabindu Valiveti, Chaitanya Duggineni, S. Tummala, S. Kosaraju, P. Bobba (+1 others)
2021 E3S Web of Conferences  
Finally, the use of transfer learning approaches to monocular depth estimation is illustrated.  ...  A complete overview of multiple deep learning methods that use transfer learning Network designs, including several combinations of encoders and decoders, is offered.  ...  Monocular Depth Estimation Transfer Learning Techniques Convolutional Neural Networks (CNNs) Researchers constructed CNN-dependent estimation networks of monocular depth that learn depth information  ... 
doi:10.1051/e3sconf/202130901069 fatcat:kn7nypnfnzgk7hmadubgkttmxe

Monocular Human Shape and Pose with Dense Mesh-borne Local Image Features [article]

Shubhendu Jena, Franck Multon, Adnane Boukhayma
2021 arXiv   pre-print
We propose to improve on graph convolution based approaches for human shape and pose estimation from monocular input, using pixel-aligned local image features.  ...  Given a single input color image, existing graph convolutional network (GCN) based techniques for human shape and pose estimation use a single convolutional neural network (CNN) generated global image  ...  Learning-based methods 1) Model-based: Model-based methods make use of a parametric 3D human body model to perform 3D human pose and shape estimation.  ... 
arXiv:2111.05319v3 fatcat:q3o3w3cxtfglnbyb7tvfpe62xi

Monocular Depth Estimation Based On Deep Learning: An Overview [article]

Chaoqiang Zhao, Qiyu Sun, Chongzhen Zhang, Yang Tang, Feng Qian
2020 arXiv   pre-print
Initially, we conclude several widely used datasets and evaluation indicators in deep learning-based depth estimation.  ...  Inferring depth information from a single image (monocular depth estimation) is an ill-posed problem.  ...  MONOCULAR DEPTH ESTIMATION BASED ON DEEP LEARNING Since humans can use priori information of the world, it is capable for them to perceive the depth information from a single image.  ... 
arXiv:2003.06620v1 fatcat:l5ei3ognova6xkyppflef5nqsq

Outdoor Monocular Depth Estimation: A Research Review [article]

Pulkit Vyas, Chirag Saxena, Anwesh Badapanda, Anurag Goswami
2022 arXiv   pre-print
the current time is on a single source, or monocular, depth estimation.  ...  While the traditional methods of estimating depth are based on depth cues and require specific equipment such as stereo cameras and configuring input according to the approach being used, the focus at  ...  Supervised Learning Supervised learning networks for monocular depth estimation are trained using the Ground Truth depth maps.  ... 
arXiv:2205.01399v1 fatcat:mwitpnwlz5cl7ahv4wd4up5nxa


Dushyant Mehta, Srinath Sridhar, Oleksandr Sotnychenko, Helge Rhodin, Mohammad Shafiei, Hans-Peter Seidel, Weipeng Xu, Dan Casas, Christian Theobalt
2017 ACM Transactions on Graphics  
Our method's accuracy is quantitatively on par with the best offline 3D monocular RGB pose estimation methods.  ...  We present the first real-time method to capture the full global 3D skeletal pose of a human in a stable, temporally consistent manner using a single RGB camera.  ...  Discriminative 2D human pose estimation is often an intermediate step to monocular 3D pose estimation.  ... 
doi:10.1145/3072959.3073596 fatcat:kviukzjktjbbrfjxcr2kgtytse

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies [article]

Yu Huang, Yue Chen
2020 arXiv   pre-print
Due to the limited space, we focus the analysis on several key areas, i.e. 2D and 3D object detection in perception, depth estimation from cameras, multiple sensor fusion on the data, feature and task  ...  Almost at the same time, deep learning has made breakthrough by several pioneers, three of them (also called fathers of deep learning), Hinton, Bengio and LeCun, won ACM Turin Award in 2019.  ...  tracking and human pose estimation (used for pedestrian movement analysis).  ... 
arXiv:2006.06091v3 fatcat:nhdgivmtrzcarp463xzqvnxlwq

Recent Advances of Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective

Wu Liu, Tao Mei
2022 ACM Computing Surveys  
Recently, benefiting from the deep learning technologies, a significant amount of research efforts have advanced the monocular human pose estimation both in 2D and 3D areas.  ...  Estimation of the human pose from a monocular camera has been an emerging research topic in the computer vision community with many applications.  ...  This paper provides a comprehensive survey on deep learning-based monocular human pose estimation for both 2D and 3D tasks.  ... 
doi:10.1145/3524497 fatcat:4pbvntngrnfp7lqhcpjmy7p2fq

Towards Better Generalization: Joint Depth-Pose Learning without PoseNet [article]

Wang Zhao, Shaohui Liu, Yezhi Shu, Yong-Jin Liu
2021 arXiv   pre-print
depth-pose learning methods under a variety of challenging scenarios, and achieves state-of-the-art results among self-supervised learning-based methods on KITTI Odometry and NYUv2 dataset.  ...  Extensive experiments show that our system not only reaches state-of-the-art performance on KITTI depth and flow estimation, but also significantly improves the generalization ability of existing self-supervised  ...  Acknowledgements This work was partially supported by NSFC (61725204, 61521002), BNRist and MOE-Key Laboratory of Pervasive Computing.  ... 
arXiv:2004.01314v2 fatcat:ria3yrzwafcdxoux2y2ctmguke

Deep 3D human pose estimation: A review

Jinbao Wang, Shujie Tan, Xiantong Zhen, Shuo Xu, Feng Zheng, Zhenyu He, Ling Shao
2021 Computer Vision and Image Understanding  
A robot can better serve and help users if it can understand 3D poses, actions and J o u r n a l P r e -p r o o f Journal Pre-proof Abstract 3D human pose estimation from a monocular image or 2D joints  ...  We argue that 3D human pose estimation from a monocular input is an inverse problem where multiple feasible solutions can exist.  ...  The 3D human pose estimation from a single monocular image suffers from inherent ambiguity, and thus more supervision signals are required.  ... 
doi:10.1016/j.cviu.2021.103225 fatcat:hvlgjuxd2zfgji6k4y4g65cs7y

Constant Velocity Constraints for Self-Supervised Monocular Depth Estimation

Hang Zhou, David Greenwood, Sarah Taylor, Han Gong
2020 European Conference on Visual Media Production  
ABSTRACT We present a new method for self-supervised monocular depth estimation.  ...  Contemporary monocular depth estimation methods use a triplet of consecutive video frames to estimate the central depth image.  ...  [Zhou et al. 2017] proposed the first self-supervised monocular depth learning that simultaneously learns both depth and camera pose estimators during training.  ... 
doi:10.1145/3429341.3429355 fatcat:gx6bcnssujbx5obuyktz2b2yyu

Deep Learning-Based Human Pose Estimation: A Survey [article]

Ce Zheng and Wenhan Wu and Chen Chen and Taojiannan Yang and Sijie Zhu and Ju Shen and Nasser Kehtarnavaz and Mubarak Shah
2022 arXiv   pre-print
Furthermore, 2D and 3D human pose estimation datasets and evaluation metrics are included.  ...  The goal of this survey paper is to provide a comprehensive review of recent deep learning-based solutions for both 2D and 3D pose estimation via a systematic analysis and comparison of these solutions  ...  [298] proposed a weakly supervised transfer learning method that uses 2D annotations of in-the-wild images as weak labels. 3D pose estimation module was connected with intermediate layers of the 2D  ... 
arXiv:2012.13392v4 fatcat:ypnqtq3sbncr5fuujif2dhqwji

In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations

Ikhsanul Habibie, Weipeng Xu, Dushyant Mehta, Gerard Pons-Moll, Christian Theobalt
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
We therefore propose a new deep learning based method for monocular 3D human pose estimation that shows high accuracy and generalizes better to in-the-wild scenes.  ...  It has a network architecture that comprises a new disentangled hidden space encoding of explicit 2D and 3D features, and uses supervision by a new learned projection model from predicted 3D pose.  ...  Such failure cases are common to many monocular 3D pose estimation approaches. Conclusion We proposed a new deep learning architecture for 3D human pose estimation from monocular color images.  ... 
doi:10.1109/cvpr.2019.01116 dblp:conf/cvpr/HabibieXMPT19 fatcat:5h5n5puhlvfz7p52duegjtvaz4
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