Understanding cities with machine eyes: A review of deep computer vision in urban analytics
Modelling urban systems has interested planners and modellers for decades. Different
models have been achieved relying on mathematics, cellular automation, complexity, and …
models have been achieved relying on mathematics, cellular automation, complexity, and …
Deep learning in visual tracking: A review
Deep learning (DL) has made breakthroughs in many computer vision tasks and also in
visual tracking. From the beginning of the research on the automatic acquisition of high …
visual tracking. From the beginning of the research on the automatic acquisition of high …
Transmot: Spatial-temporal graph transformer for multiple object tracking
Tracking multiple objects in videos relies on modeling the spatial-temporal interactions of
the objects. In this paper, we propose TransMOT, which leverages powerful graph …
the objects. In this paper, we propose TransMOT, which leverages powerful graph …
Mots: Multi-object tracking and segmentation
This paper extends the popular task of multi-object tracking to multi-object tracking and
segmentation (MOTS). Towards this goal, we create dense pixel-level annotations for two …
segmentation (MOTS). Towards this goal, we create dense pixel-level annotations for two …
End-to-end learning of driving models with surround-view cameras and route planners
For human drivers, having rear and side-view mirrors is vital for safe driving. They deliver a
more complete view of what is happening around the car. Human drivers also heavily exploit …
more complete view of what is happening around the car. Human drivers also heavily exploit …
Probabilistic tracklet scoring and inpainting for multiple object tracking
Despite the recent advances in multiple object tracking (MOT), achieved by joint detection
and tracking, dealing with long occlusions remains a challenge. This is due to the fact that …
and tracking, dealing with long occlusions remains a challenge. This is due to the fact that …
TransCenter: Transformers with dense representations for multiple-object tracking
Transformers have proven superior performance for a wide variety of tasks since they were
introduced. In recent years, they have drawn attention from the vision community in tasks …
introduced. In recent years, they have drawn attention from the vision community in tasks …
Towards discriminative representation: Multi-view trajectory contrastive learning for online multi-object tracking
Discriminative representation is crucial for the association step in multi-object tracking.
Recent work mainly utilizes features in single or neighboring frames for constructing metric …
Recent work mainly utilizes features in single or neighboring frames for constructing metric …
[HTML][HTML] Recent trends in crowd analysis: A review
When overpopulated cities face frequent crowded events like strikes, demonstrations,
parades or other sorts of people gatherings, they are confronted to multiple security issues …
parades or other sorts of people gatherings, they are confronted to multiple security issues …
Posetrack21: A dataset for person search, multi-object tracking and multi-person pose tracking
Current research evaluates person search, multi-object tracking and multi-person pose
estimation as separate tasks and on different datasets although these tasks are very akin to …
estimation as separate tasks and on different datasets although these tasks are very akin to …