269 citations · 1k across the 14 of their papers we have counts for
16 papers
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…
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…
HandFlow: Quantifying View-Dependent 3D Ambiguity in Two-Hand Reconstruction with Normalizing Flow
Jiayi Wang, Diogo Luvizon, Franziska Mueller +4
Reconstructing two-hand interactions from a single image is a challenging problem due to ambiguities that stem from projective geometry and heavy occlusions. Existing methods are d…
RGB2Hands: Real-Time Tracking of 3D Hand Interactions from Monocular RGB Video
Jiayi Wang, Franziska Mueller, Florian Bernard +6
Tracking and reconstructing the 3D pose and geometry of two hands in interaction is a challenging problem that has a high relevance for several human-computer interaction applicati…
Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera
Franziska Mueller, Micah Davis, Florian Bernard +5
We present a novel method for real-time pose and shape reconstruction of two strongly interacting hands. Our approach is the first two-hand tracking solution that combines an exten…
Differentiable Event Stream Simulator for Non-Rigid 3D Tracking
Jalees Nehvi, Vladislav Golyanik, Franziska Mueller +3
This paper introduces the first differentiable simulator of event streams, i.e., streams of asynchronous brightness change signals recorded by event cameras. Our differentiable sim…
EventHands: Real-Time Neural 3D Hand Pose Estimation from an Event Stream
Viktor Rudnev, Vladislav Golyanik, Jiayi Wang +4
3D hand pose estimation from monocular videos is a long-standing and challenging problem, which is now seeing a strong upturn. In this work, we address it for the first time using…
Generative Model-Based Loss to the Rescue: A Method to Overcome Annotation Errors for Depth-Based Hand Pose Estimation
Jiayi Wang, Franziska Mueller, Florian Bernard +1
We propose to use a model-based generative loss for training hand pose estimators on depth images based on a volumetric hand model. This additional loss allows training of a hand p…
Convex Optimisation for Inverse Kinematics
Tarun Yenamandra, Florian Bernard, Jiayi Wang +2
We consider the problem of inverse kinematics (IK), where one wants to find the parameters of a given kinematic skeleton that best explain a set of observed 3D joint locations. The…
XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera
Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller +7
We present a real-time approach for multi-person 3D motion capture at over 30 fps using a single RGB camera. It operates successfully in generic scenes which may contain occlusions…
GANerated Hands for Real-time 3D Hand Tracking from Monocular RGB
Franziska Mueller, Florian Bernard, Oleksandr Sotnychenko +4
We address the highly challenging problem of real-time 3D hand tracking based on a monocular RGB-only sequence. Our tracking method combines a convolutional neural network with a k…
Single-Shot Multi-Person 3D Pose Estimation From Monocular RGB
Dushyant Mehta, Oleksandr Sotnychenko, Franziska Mueller +4
We propose a new single-shot method for multi-person 3D pose estimation in general scenes from a monocular RGB camera. Our approach uses novel occlusion-robust pose-maps (ORPM) whi…
HandSeg: An Automatically Labeled Dataset for Hand Segmentation from Depth Images
Abhishake Kumar Bojja, Franziska Mueller, Sri Raghu Malireddi +5
We propose an automatic method for generating high-quality annotations for depth-based hand segmentation, and introduce a large-scale hand segmentation dataset. Existing datasets a…
Real-time Hand Tracking under Occlusion from an Egocentric RGB-D Sensor
Franziska Mueller, Dushyant Mehta, Oleksandr Sotnychenko +3
We present an approach for real-time, robust and accurate hand pose estimation from moving egocentric RGB-D cameras in cluttered real environments. Existing methods typically fail…
Real-time Joint Tracking of a Hand Manipulating an Object from RGB-D Input
Srinath Sridhar, Franziska Mueller, Michael Zollhöfer +3
Real-time simultaneous tracking of hands manipulating and interacting with external objects has many potential applications in augmented reality, tangible computing, and wearable c…
Fast and Robust Hand Tracking Using Detection-Guided Optimization
Srinath Sridhar, Franziska Mueller, Antti Oulasvirta +1
Markerless tracking of hands and fingers is a promising enabler for human-computer interaction. However, adoption has been limited because of tracking inaccuracies, incomplete cove…