no code implementations • 22 Dec 2023 • Soshi Shimada, Franziska Mueller, Jan Bednarik, Bardia Doosti, Bernd Bickel, Danhang Tang, Vladislav Golyanik, Jonathan Taylor, Christian Theobalt, Thabo Beeler
To improve the naturalness of the synthesized 3D hand object motions, this work proposes MACS the first MAss Conditioned 3D hand and object motion Synthesis approach.
no code implementations • ICCV 2023 • Tze Ho Elden Tse, Franziska Mueller, Zhengyang Shen, Danhang Tang, Thabo Beeler, Mingsong Dou, yinda zhang, Sasa Petrovic, Hyung Jin Chang, Jonathan Taylor, Bardia Doosti
We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images.
no code implementations • 15 Oct 2020 • Bardia Doosti, Ching-Hui Chen, Raviteja Vemulapalli, Xuhui Jia, Yukun Zhu, Bradley Green
In this work, we focus on the task of image-based mutual gaze detection, and propose a simple and effective approach to boost the performance by using an auxiliary 3D gaze estimation task during the training phase.
no code implementations • 9 Jun 2020 • Majid Mirbagheri, Bardia Doosti
Human brain employs perceptual information about the head and eye movements to update the spatial relationship between the individual and the surrounding environment.
1 code implementation • CVPR 2020 • Bardia Doosti, Shujon Naha, Majid Mirbagheri, David Crandall
Hand-object pose estimation (HOPE) aims to jointly detect the poses of both a hand and of a held object.
no code implementations • 3 Mar 2019 • Bardia Doosti
The success of Deep Convolutional Neural Networks (CNNs) in recent years in almost all the Computer Vision tasks on one hand, and the popularity of low-cost consumer depth cameras on the other, has made Hand Pose Estimation a hot topic in computer vision field.
no code implementations • 11 Jul 2018 • Bardia Doosti, Tao Dong, Biplab Deka, Jeffrey Nichols
UI design languages, such as Google's Material Design, make applications both easier to develop and easier to learn by providing a set of standard UI components.