CameraPose: Weakly-Supervised Monocular 3D Human Pose Estimation by Leveraging In-the-wild 2D Annotations
Author:
Affiliation:
1. University of Washington,Department of Electrical and Computer Engineering,WA,USA
2. Amazon Lab126,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10030081/10030084/10030754.pdf?arnumber=10030754
Reference37 articles.
1. In the Wild Human Pose Estimation Using Explicit 2D Features and Intermediate 3D Representations
2. Canonpose: Self-supervised monocular 3d human pose estimation in the wild;wandt;CoRR,2020
3. Fast Lifting for 3D Hand Pose Estimation in AR/VR Applications
4. An Efficient 3D Synthetic Model Generation Pipeline for Human Pose Data Augmentation
5. Human3.6M: Large Scale Datasets and Predictive Methods for 3D Human Sensing in Natural Environments
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1. Deep learning for 3D human pose estimation and mesh recovery: A survey;Neurocomputing;2024-09
2. Learning Temporal–Spatial Contextual Adaptation for Three-Dimensional Human Pose Estimation;Sensors;2024-07-08
3. Uncalibrated Multi-view 3D Human Pose Estimation with Geometry Driven Attention;2024 IEEE 18th International Conference on Automatic Face and Gesture Recognition (FG);2024-05-27
4. Enhancing 3D Content Creation in Blender With Monocular RGB Image Keypoints: A Multi-Stage Approach;2024 IEEE International Conference on Advanced Systems and Emergent Technologies (IC_ASET);2024-04-27
5. A Normalization Strategy for Weakly Supervised 3D Hand Pose Estimation;Applied Sciences;2024-04-24
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