4 accepted papers
Human action recognition (HAR) is a critical task in the field of robotics. Traditionally, HAR methods rely on either perceptual features from RGB images or skeletal features. While RGB-based features are typically represented in 2D Euclidean space, few approaches differentiate between methods devel
The advent of unmanned aerial vehicles (UAVs) has initiated a revolutionary era in human action recognition, profoundly influencing various domains. This transition underscores the critical necessity for comprehensive benchmarks crucial for formulating and evaluating UAV-centric models tailored to h…
Action recognition and human pose estimation are closely related but both problems are generally handled as distinct tasks in the literature. In this work, we propose a multitask framework for jointly 2D and 3D pose estimation from still images and human action recognition from video sequences. We s…
This paper addresses the problem of reassembling images from disjointed fragments. More specifically, given an unordered set of fragments, we aim at reassembling one or several possibly incomplete images. The main contributions of this work are: 1) several deep neural architectures to predict the re…