Visual affordance and function understanding: A survey
Nowadays, robots are dominating the manufacturing, entertainment, and healthcare
industries. Robot vision aims to equip robots with the capabilities to discover information …
industries. Robot vision aims to equip robots with the capabilities to discover information …
KD-PAR: A knowledge distillation-based pedestrian attribute recognition model with multi-label mixed feature learning network
In this paper, a novel knowledge distillation (KD)-based pedestrian attribute recognition
(PAR) model is developed, where a multi-label mixed feature learning network (MMFL-Net) …
(PAR) model is developed, where a multi-label mixed feature learning network (MMFL-Net) …
Transferable joint attribute-identity deep learning for unsupervised person re-identification
Most existing person re-identification (re-id) methods require supervised model learning
from a separate large set of pairwise labelled training data for every single camera pair. This …
from a separate large set of pairwise labelled training data for every single camera pair. This …
Pose-normalized image generation for person re-identification
Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired
training data and learning discriminative identity-sensitive and view-invariant features in the …
training data and learning discriminative identity-sensitive and view-invariant features in the …
Beyond human parts: Dual part-aligned representations for person re-identification
Person re-identification is a challenging task due to various complex factors. Recent studies
have attempted to integrate human parsing results or externally defined attributes to help …
have attempted to integrate human parsing results or externally defined attributes to help …
Dynamic curriculum learning for imbalanced data classification
Human attribute analysis is a challenging task in the field of computer vision. One of the
significant difficulties is brought from largely imbalance-distributed data. Conventional …
significant difficulties is brought from largely imbalance-distributed data. Conventional …
[HTML][HTML] Deep learning-based crowd scene analysis survey
Recently, our world witnessed major events that attracted a lot of attention towards the
importance of automatic crowd scene analysis. For example, the COVID-19 breakout and …
importance of automatic crowd scene analysis. For example, the COVID-19 breakout and …
Class rectification hard mining for imbalanced deep learning
Recognising detailed facial or clothing attributes in images of people is a challenging task
for computer vision, especially when the training data are both in very large scale and …
for computer vision, especially when the training data are both in very large scale and …
Improving pedestrian attribute recognition with weakly-supervised multi-scale attribute-specific localization
Pedestrian attribute recognition has been an emerging research topic in the area of video
surveillance. To predict the existence of a particular attribute, it is demanded to localize the …
surveillance. To predict the existence of a particular attribute, it is demanded to localize the …
Spatial and semantic consistency regularizations for pedestrian attribute recognition
While recent studies on pedestrian attribute recognition have shown remarkable progress in
leveraging complicated networks and attention mechanisms, most of them neglect the inter …
leveraging complicated networks and attention mechanisms, most of them neglect the inter …