Multiple object tracking: A literature review
Abstract Multiple Object Tracking (MOT) has gained increasing attention due to its academic
and commercial potential. Although different approaches have been proposed to tackle this …
and commercial potential. Although different approaches have been proposed to tackle this …
[HTML][HTML] Multi-camera multi-object tracking: a review of current trends and future advances
The nascent applicability of multi-camera tracking (MCT) in numerous real-world
applications makes it a significant computer vision problem. While visual tracking of objects …
applications makes it a significant computer vision problem. While visual tracking of objects …
Joint discriminative and generative learning for person re-identification
Person re-identification (re-id) remains challenging due to significant intra-class variations
across different cameras. Recently, there has been a growing interest in using generative …
across different cameras. Recently, there has been a growing interest in using generative …
Joint disentangling and adaptation for cross-domain person re-identification
Although a significant progress has been witnessed in supervised person re-identification
(re-id), it remains challenging to generalize re-id models to new domains due to the huge …
(re-id), it remains challenging to generalize re-id models to new domains due to the huge …
Sg-net: Spatial granularity network for one-stage video instance segmentation
Video instance segmentation (VIS) is a new and critical task in computer vision. To date, top-
performing VIS methods extend the two-stage Mask R-CNN by adding a tracking branch …
performing VIS methods extend the two-stage Mask R-CNN by adding a tracking branch …
The 7th ai city challenge
Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …
Pamtri: Pose-aware multi-task learning for vehicle re-identification using highly randomized synthetic data
In comparison with person re-identification (ReID), which has been widely studied in the
research community, vehicle ReID has received less attention. Vehicle ReID is challenging …
research community, vehicle ReID has received less attention. Vehicle ReID is challenging …
Exploit the connectivity: Multi-object tracking with trackletnet
Multi-object tracking (MOT) is an important topic and critical task related to both static and
moving camera applications, such as traffic flow analysis, autonomous driving and robotic …
moving camera applications, such as traffic flow analysis, autonomous driving and robotic …
Simulating content consistent vehicle datasets with attribute descent
This paper uses a graphic engine to simulate a large amount of training data with free
annotations. Between synthetic and real data, there is a two-level domain gap, ie, content …
annotations. Between synthetic and real data, there is a two-level domain gap, ie, content …
6-DoF pose estimation of household objects for robotic manipulation: An accessible dataset and benchmark
We present a new dataset for 6-DoF pose estimation of known objects, with a focus on
robotic manipulation research. We propose a set of toy grocery objects, whose physical …
robotic manipulation research. We propose a set of toy grocery objects, whose physical …