Human motion capture either requires multi-camera systems or is unreliab...
It is now possible to reconstruct dynamic human motion and shape from a
...
Modern deep neural networks are prone to being overconfident despite the...
We tackle the task of scene flow estimation from point clouds. Given a s...
Traditionally, monocular 3D human pose estimation employs a machine lear...
Industrial defect detection is commonly addressed with anomaly detection...
Structured representations such as keypoints are widely used in pose
tra...
Generative adversarial networks (GANs) can now generate photo-realistic
...
Injury analysis may be one of the most beneficial applications of deep
l...
This paper addresses the problem of cross-dataset generalization of 3D h...
Human pose estimation from single images is a challenging problem that i...
Segmenting an image into its parts is a frequent preprocess for high-lev...
In industrial manufacturing processes, errors frequently occur at
unpred...
3D human pose estimation from monocular images is a highly ill-posed pro...
Generative adversarial networks (GANs) have attained photo-realistic qua...
Sensory substitution can help persons with perceptual deficits. In this ...
Human pose estimation from single images is a challenging problem in com...
The detection of manufacturing errors is crucial in fabrication processe...
This paper proposes a weakly-supervised learning framework for dynamics
...
In this paper we propose Structuring AutoEncoders (SAE). SAEs are neural...
This paper addresses the problem of 3D human pose estimation from single...
This paper deals with motion capture of kinematic chains (e.g. human
ske...