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Found 6 papers, 1 papers with code
PoseGraphNet++: Enriching 3D Human Pose with Orientation Estimation
Existing kinematic skeleton-based 3D human pose estimation methods only predict joint positions.
Occlusion Robust 3D Human Pose Estimation with StridedPoseGraphFormer and Data Augmentation
We show that our proposed method compares favorably with the state-of-the-art (SoA).
Graph Neural Networks for Relational Inductive Bias in Vision-based Deep Reinforcement Learning of Robot Control
We derive a graph representation that models the physical structure of the manipulator and combines the robot's internal state with a low-dimensional description of the visual scene generated by an image encoding network.
Vogtareuth Rehab Depth Datasets: Benchmark for Marker-less Posture Estimation in Rehabilitation
We evaluate it on our rehab datasets, and observe that the performance degrades significantly from non-rehab to rehab, highlighting the need for these datasets.
3D Human Pose Regression using Graph Convolutional Network
We propose one such graph convolutional network named PoseGraphNet for 3D human pose regression from 2D poses.
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3D Human Pose Estimation
on Human3.6M
Multi-label Object Attribute Classification using a Convolutional Neural Network
With this inspiration, a deep convolutional neural network for low-level object attribute classification, called the Deep Attribute Network (DAN), is proposed.
