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RGB-based 3D Hand Pose Estimation via Privileged Learning with Depth Images
Shanxin Yuan, Bjorn Stenger, Tae-Kyun Kim
This paper proposes a method for hand pose estimation from RGB images that uses both external large-scale depth image datasets and paired depth and RGB images as privileged informa…
HANDS18: Methods, Techniques and Applications for Hand Observation
Iason Oikonomidis, Guillermo Garcia-Hernando, Angela Yao +3
This report outlines the proceedings of the Fourth International Workshop on Observing and Understanding Hands in Action (HANDS 2018). The fourth instantiation of this workshop att…
A Summary of the 4th International Workshop on Recovering 6D Object Pose
Tomas Hodan, Rigas Kouskouridas, Tae-Kyun Kim +12
This document summarizes the 4th International Workshop on Recovering 6D Object Pose which was organized in conjunction with ECCV 2018 in Munich. The workshop featured four invited…
Task-Oriented Hand Motion Retargeting for Dexterous Manipulation Imitation
Dafni Antotsiou, Guillermo Garcia-Hernando, Tae-Kyun Kim
Human hand actions are quite complex, especially when they involve object manipulation, mainly due to the high dimensionality of the hand and the vast action space that entails. Im…
BOP: Benchmark for 6D Object Pose Estimation
Tomas Hodan, Frank Michel, Eric Brachmann +13
We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. The training data consists of a texture-mapped 3D object model or images of the obj…
Category-level 6D Object Pose Recovery in Depth Images
Caner Sahin, Tae-Kyun Kim
Intra-class variations, distribution shifts among source and target domains are the major challenges of category-level tasks. In this study, we address category-level full 6D objec…
Multi-Task Deep Networks for Depth-Based 6D Object Pose and Joint Registration in Crowd Scenarios
Juil Sock, Kwang In Kim, Caner Sahin +1
In bin-picking scenarios, multiple instances of an object of interest are stacked in a pile randomly, and hence, the instances are inherently subjected to the challenges: severe oc…
Augmented Skeleton Space Transfer for Depth-based Hand Pose Estimation
Seungryul Baek, Kwang In Kim, Tae-Kyun Kim
Crucial to the success of training a depth-based 3D hand pose estimator (HPE) is the availability of comprehensive datasets covering diverse camera perspectives, shapes, and pose v…
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model
Baris Gecer, Binod Bhattarai, Josef Kittler +1
We propose a novel end-to-end semi-supervised adversarial framework to generate photorealistic face images of new identities with wide ranges of expressions, poses, and illuminatio…