activity
20182023
most citedHand Pose Estimation: A Survey

33 citations · 42 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2023

MACS: Mass Conditioned 3D Hand and Object Motion Synthesis

Soshi Shimada, Franziska Mueller, Jan Bednarik +7

The physical properties of an object, such as mass, significantly affect how we manipulate it with our hands. Surprisingly, this aspect has so far been neglected in prior work on 3…

cs.CV2023★ 6 cited

Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images

Tze Ho Elden Tse, Franziska Mueller, Zhengyang Shen +8

We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images. Unlike existing hand pose estimation methods, where one typical…

cs.CV2020

Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze

Bardia Doosti, Ching-Hui Chen, Raviteja Vemulapalli +3

Mutual gaze detection, i.e., predicting whether or not two people are looking at each other, plays an important role in understanding human interactions. In this work, we focus on…

cs.SD2020

C-SL: Contrastive Sound Localization with Inertial-Acoustic Sensors

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. Based on this…

cs.CV2020

HOPE-Net: A Graph-based Model for Hand-Object Pose Estimation

Bardia Doosti, Shujon Naha, Majid Mirbagheri +1

Hand-object pose estimation (HOPE) aims to jointly detect the poses of both a hand and of a held object. In this paper, we propose a lightweight model called HOPE-Net which jointly…

cs.CV2019★ 33 cited

Hand Pose Estimation: A Survey

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…

cs.HC2018★ 3 cited

A Computational Method for Evaluating UI Patterns

Bardia Doosti, Tao Dong, Biplab Deka +1

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. Nonetheless, it is…