Search
Results
-
Self-supervised 3D hand pose estimation through training by fitting
(2019)Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019)Conference Paper -
Dense 3D Regression for Hand Pose Estimation
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionConference Paper -
Crossing Nets: Combining GANs and VAEs with a Shared Latent Space for Hand Pose Estimation
(2017)2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)State-of-the-art methods for 3D hand pose estimation from depth images require large amounts of annotated training data. We propose to model the statistical relationships of 3D hand poses and corresponding depth images using two deep generative models with a shared latent space. By design, our architecture allows for learning from unlabeled image data in a semi-supervised manner. Assuming a one-to-one mapping between a pose and a depth ...Conference Paper -
Self-Supervised 3D Hand Pose Estimation Through Training by Fitting
(2019)We present a self-supervision method for 3D hand pose estimation from depth maps. We begin with a neural network initialized with synthesized data and fine-tune it on real but unlabelled depth maps by minimizing a set of datafitting terms. By approximating the hand surface with a set of spheres, we design a differentiable hand renderer to align estimates by comparing the rendered and input depth maps. In addition, we place a set of priors ...Conference Paper