Structure-Aware 3D Hourglass Network for Hand Pose Estimation from Single Depth Image
In this paper, we propose a novel structure-aware 3D hourglass network for hand pose estimation from a single depth image, which achieves state-of-the-art results on MSRA and NYU datasets. Compared to existing works that perform image-to-coordination regression, our network takes 3D voxel as input and directly regresses 3D heatmap for each joint. To be specific, we use hourglass network as our backbone network and modify it into 3D form. We explicitly model tree-like finger bone into the network as well as in the loss function in an end-to-end manner, in order to take the skeleton constraints into consideration. Final estimation can then be easily obtained from voxel density map with simple post-processing. Experimental results show that the proposed structure-aware 3D hourglass network is able to achieve a mean joint error of 7.4 mm in MSRA and 8.9 mm in NYU datasets, respectively.
Code (0)
등록된 구현이 없습니다.
Tasks
Hand Pose EstimationPose EstimationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
SPCNet:Spatial Preserve and Content-aware Network for Human Pose Estimation
Human pose estimation is a fundamental yet challenging task in computer vision. Although deep learning techniques have made great progress in this area, difficult scenarios (e.g., invisible keypoints, occlusions, complex…
Pose EstimationAdaptive Wasserstein Hourglass for Weakly Supervised Hand Pose Estimation from Monocular RGB
Insufficient labeled training datasets is one of the bottlenecks of 3D hand pose estimation from monocular RGB images. Synthetic datasets have a large number of images with precise annotations, but the obvious difference…
3D Hand Pose EstimationDomain AdaptationHand Pose EstimationPose EstimationMulti-Scale Stacked Hourglass Network for Human Pose Estimation
Stacked hourglass network has become an important model for Human pose estimation. The estimation of human body posture depends on the global information of the keypoints type and the local information of the keypoints l…
Pose EstimationSingle upper limb pose estimation method based on improved stacked hourglass network
At present, most high-accuracy single-person pose estimation methods have high computational complexity and insufficient real-time performance due to the complex structure of the network model. However, a single-person p…
Pose EstimationQuantizationAttention-Enhanced Lightweight Hourglass Network for Human Pose Estimation
Pose estimation is a critical task in computer vision with a wide range of applications from activity monitoring to human-robot interaction. However,most of the existing methods are computationally expensive or have comp…
Pose Estimation