5 citations · 7 across the 2 of their papers we have counts for
5 papers
A Symbolic Temporal Pooling method for Video-based Person Re-Identification
S V Aruna Kumar, Ehsan Yaghoubi, Hugo Proença
In video-based person re-identification, both the spatial and temporal features are known to provide orthogonal cues to effective representations. Such representations are currentl…
The P-DESTRE: A Fully Annotated Dataset for Pedestrian Detection, Tracking, Re-Identification and Search from Aerial Devices
S. V. Aruna Kumar, Ehsan Yaghoubi, Abhijit Das +2
Over the last decades, the world has been witnessing growing threats to the security in urban spaces, which has augmented the relevance given to visual surveillance solutions able…
An Attention-Based Deep Learning Model for Multiple Pedestrian Attributes Recognition
Ehsan Yaghoubi, Diana Borza, João Neves +2
The automatic characterization of pedestrians in surveillance footage is a tough challenge, particularly when the data is extremely diverse with cluttered backgrounds, and subjects…
A Quadruplet Loss for Enforcing Semantically Coherent Embeddings in Multi-output Classification Problems
Hugo Proença, Ehsan Yaghoubi, Pendar Alirezazadeh
This paper describes one objective function for learning semantically coherent feature embeddings in multi-output classification problems, i.e., when the response variables have di…
Person Re-identification: Implicitly Defining the Receptive Fields of Deep Learning Classification Frameworks
Ehsan Yaghoubi, Diana Borza, Aruna Kumar +1
The \emph{receptive fields} of deep learning classification models determine the regions of the input data that have the most significance for providing correct decisions. The prim…