Search Results for author:
Found 6 papers, 3 papers with code
3D human pose estimation from depth maps using a deep combination of poses
This work addresses the problem of 3D human pose estimation from depth maps employing a Deep Learning approach.
LAEO-Net++: revisiting people Looking At Each Other in videos
For this purpose, we propose LAEO-Net++, a new deep CNN for determining LAEO in videos.
LAEO-Net: revisiting people Looking At Each Other in videos
For this purpose, we propose LAEO-Net, a new deep CNN for determining LAEO in videos.
iLGaCo: Incremental Learning of Gait Covariate Factors
In this paper, we propose iLGaCo, the first incremental learning approach of covariate factors for gait recognition, where the deep model can be updated with new information without re-training it from scratch by using the whole dataset.
Lightweight Structure-Aware Attention for Visual Understanding
Vision Transformers (ViTs) have become a dominant paradigm for visual representation learning with self-attention operators.
Cross-Modality Gait Recognition: Bridging LiDAR and Camera Modalities for Human Identification
Current gait recognition research mainly focuses on identifying pedestrians captured by the same type of sensor, neglecting the fact that individuals may be captured by different sensors in order to adapt to various environments.
