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- Occluded human pose estimation based on part-aware discrete diffusion . . .
Our method provides a novel solution for pose estimation in complex environments In this work, we focus on reconstructing human poses from RGB images, with particular attention given to the ambiguity issues caused by complex scenes such as occlusions
- A comprehensive framework for occluded human pose estimation
In this paper, we propose a comprehensive framework DAG (Data, Attention, Graph) to address the performance degradation caused by occlusion Specifically, we introduce the mask joints with instance paste data augmentation technique to simulate occlusion scenarios
- Rethinking Visibility in Human Pose Estimation: Occluded Pose Reasoning . . .
Occlusion is a common challenge in human pose estima-tion Curiously, learning from occluded keypoints hinders a model to detect visible keypoints We speculate that the im-pairment is likely due to a forced correlation between key-points and visual features of the occluders
- A COMPREHENSIVE FRAMEWORK FOR OCCLUDED HUMAN POSE ESTIMATION - SigPort
In this paper, we propose a comprehensive frame-work DAG (Data, Attention, Graph) to address the perfor-mance degradation caused by occlusion Specifically, we in-troduce the mask joints with instance paste data augmentation technique to simulate occlusion scenarios
- Object-Occluded Human Shape and Pose Estimation With Probabilistic . . .
In this paper, we focus on the problem of directly estimating the object-occluded human shape and pose from single color images Our key idea is to utilize a partial UV map to represent an object-occluded human body, and the full 3D human shape estimation is ultimately converted as an image inpainting problem
- CONet: Crowd and occlusion-aware network for occluded human pose estimation
To effectively estimate poses in crowded and occluded scenes, we propose the Crowded and Occlusion-aware Head (COHead), which employs a dual-branch structure to detect key points for multiple people
- Occluded human pose estimation based on part-aware discrete diffusion . . .
Combining human priors with diffusion model boosts pose accuracy in occluded scenes Our method provides a novel solution for pose estimation in complex environments
- Estimating Human Pose from Occluded Images - University of California . . .
We address the problem of recovering 3D human pose from single 2D images, in which the pose estimation problem is formulated as a direct nonlinear regression from image observation to 3D joint positions
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