Search Results for author:
Found 7 papers, 2 papers with code
Reconstructing Three-Dimensional Models of Interacting Humans
Understanding 3d human interactions is fundamental for fine-grained scene analysis and behavioural modeling.
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision
We introduce a novel unified model for self- and interpenetration-collisions based on a mesh approximation computed by applying decimation operators.
AIFit: Automatic 3D Human-Interpretable Feedback Models for Fitness Training
AIFit is able to reconstruct 3d human pose and motion, reliably segment exercise repetitions, and identify in real-time the deviations between standards learnt from trainers, and the execution of a trainee.
Learning Complex 3D Human Self-Contact
Monocular estimation of three dimensional human self-contact is fundamental for detailed scene analysis including body language understanding and behaviour modeling.
3D Human Sensing, Action and Emotion Recognition in Robot Assisted Therapy of Children With Autism
We introduce new, fine-grained action and emotion recognition tasks defined on non-staged videos, recorded during robot-assisted therapy sessions of children with autism.
A Parallel Framework for Parametric Maximum Flow Problems in Image Segmentation
This paper presents a framework that supports the implementation of parallel solutions for the widespread parametric maximum flow computational routines used in image segmentation algorithms.
Human3.6m: Large scale datasets and predictive methods for 3D human sensing in natural environments
We introduce a new dataset, Human3. 6M, of 3. 6 Million accurate 3D Human poses, acquired by recording the performance of 5 female and 6 male subjects, under 4 different viewpoints, for training realistic human sensing systems and for evaluating the next generation of human pose estimation models and algorithms.
