MuTr: Multi-Stage Transformer for Hand Pose Estimation from Full-Scene Depth Image

1 code implementation • Sensors 2023 • Jakub Kanis, Ivan Gruber, Zdeněk Krňoul, Matyáš Boháček, Jakub Straka, Marek Hrúz

This work presents a novel transformer-based method for hand pose estimation—DePOTR.

Hand Pose Estimation

One Model is Not Enough: Ensembles for Isolated Sign Language Recognition

no code implementations • Sensors 2022 • Marek Hrúz, Ivan Gruber, Jakub Kanis, Matyáš Boháček, Miroslav Hlaváč, Zdeněk Krňoul

In this paper, we dive into sign language recognition, focusing on the recognition of isolated signs.

Sign Language Recognition

Hand Pose Estimation in the Task of Egocentric Actions

no code implementations • IEEE Access 2021 • Marek Hrúz, Jakub Kanis, Zdenĕk Krňoul

In this article we tackle the problem of hand pose estimation when the hand is interacting with various objects from egocentric viewpoint.

3D Hand Pose Estimation Task 2

Sign Language Motion Capture Dataset for Data-driven Synthesis

no code implementations • LREC 2020 • Pavel Jedli{\v{c}}ka, Zden{\v{e}}k Kr{\v{n}}oul, Jakub Kanis, Milo{\v{s}} {\v{Z}}elezn{\'y}

The dataset was recorded using the state-of-the-art motion capture (MoCap) technology to provide the most precise trajectories of the motion.

Measuring Generalisation to Unseen Viewpoints, Articulations, Shapes and Objects for 3D Hand Pose Estimation under Hand-Object Interaction

no code implementations • ECCV 2020 • Anil Armagan, Guillermo Garcia-Hernando, Seungryul Baek, Shreyas Hampali, Mahdi Rad, Zhaohui Zhang, Shipeng Xie, Mingxiu Chen, Boshen Zhang, Fu Xiong, Yang Xiao, Zhiguo Cao, Junsong Yuan, Pengfei Ren, Weiting Huang, Haifeng Sun, Marek Hrúz, Jakub Kanis, Zdeněk Krňoul, Qingfu Wan, Shile Li, Linlin Yang, Dongheui Lee, Angela Yao, Weiguo Zhou, Sijia Mei, Yun-hui Liu, Adrian Spurr, Umar Iqbal, Pavlo Molchanov, Philippe Weinzaepfel, Romain Brégier, Grégory Rogez, Vincent Lepetit, Tae-Kyun Kim

To address these issues, we designed a public challenge (HANDS'19) to evaluate the abilities of current 3D hand pose estimators (HPEs) to interpolate and extrapolate the poses of a training set.

3D Hand Pose Estimation