266 citations · 981 across the 59 of their papers we have counts for
8 papers · 1 filter
Set Augmented Triplet Loss for Video Person Re-Identification
Pengfei Fang, Pan Ji, Lars Petersson +1
Modern video person re-identification (re-ID) machines are often trained using a metric learning approach, supervised by a triplet loss. The triplet loss used in video re-ID is usu…
Channel Recurrent Attention Networks for Video Pedestrian Retrieval
Pengfei Fang, Pan Ji, Jieming Zhou +2
Full attention, which generates an attention value per element of the input feature maps, has been successfully demonstrated to be beneficial in visual tasks. In this work, we prop…
Cross-Correlated Attention Networks for Person Re-Identification
Jieming Zhou, Soumava Kumar Roy, Pengfei Fang +2
Deep neural networks need to make robust inference in the presence of occlusion, background clutter, pose and viewpoint variations -- to name a few -- when the task of person re-id…
Mosaic Super-resolution via Sequential Feature Pyramid Networks
Mehrdad Shoeiby, Mohammad Ali Armin, Sadegh Aliakbarian +2
Advances in the design of multi-spectral cameras have led to great interests in a wide range of applications, from astronomy to autonomous driving. However, such cameras inherently…
Attention Based Real Image Restoration
Saeed Anwar, Nick Barnes, Lars Petersson
Deep convolutional neural networks perform better on images containing spatially invariant degradations, also known as synthetic degradations; however, their performance is limited…
Transferring Cross-domain Knowledge for Video Sign Language Recognition
Dongxu Li, Xin Yu, Chenchen Xu +2
Word-level sign language recognition (WSLR) is a fundamental task in sign language interpretation. It requires models to recognize isolated sign words from videos. However, annotat…
A Systematic Evaluation: Fine-Grained CNN vs. Traditional CNN Classifiers
Saeed Anwar, Nick Barnes, Lars Petersson
To make the best use of the underlying minute and subtle differences, fine-grained classifiers collect information about inter-class variations. The task is very challenging due to…
Neural Memory Networks for Seizure Type Classification
David Ahmedt-Aristizabal, Tharindu Fernando, Simon Denman +3
Classification of seizure type is a key step in the clinical process for evaluating an individual who presents with seizures. It determines the course of clinical diagnosis and tre…