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Found 7 papers, 6 papers with code
Learning 3D Human Pose Estimation from Dozens of Datasets using a Geometry-Aware Autoencoder to Bridge Between Skeleton Formats
Our approach scales to an extreme multi-dataset regime, where we use 28 3D human pose datasets to supervise one model, which outperforms prior work on a range of benchmarks, including the challenging 3D Poses in the Wild (3DPW) dataset.
MeTRAbs: Metric-Scale Truncation-Robust Heatmaps for Absolute 3D Human Pose Estimation
Heatmap representations have formed the basis of human pose estimation systems for many years, and their extension to 3D has been a fruitful line of recent research.
Ranked #1 on
3D Human Pose Estimation
on 3D Poses in the Wild Challenge
(MPJPE metric)
Reposing Humans by Warping 3D Features
We address the problem of reposing an image of a human into any desired novel pose.
Metric-Scale Truncation-Robust Heatmaps for 3D Human Pose Estimation
Furthermore, as the image space is decoupled from the heatmap space, the network can learn to reason about joints beyond the image boundary.
Ranked #151 on
3D Human Pose Estimation
on Human3.6M
Visual Person Understanding through Multi-Task and Multi-Dataset Learning
We address the problem of learning a single model for person re-identification, attribute classification, body part segmentation, and pose estimation.
Synthetic Occlusion Augmentation with Volumetric Heatmaps for the 2018 ECCV PoseTrack Challenge on 3D Human Pose Estimation
In this paper we present our winning entry at the 2018 ECCV PoseTrack Challenge on 3D human pose estimation.
Ranked #211 on
3D Human Pose Estimation
on Human3.6M
How Robust is 3D Human Pose Estimation to Occlusion?
Occlusion is commonplace in realistic human-robot shared environments, yet its effects are not considered in standard 3D human pose estimation benchmarks.
Ranked #222 on
3D Human Pose Estimation
on Human3.6M
