3 research outputs found
ReIDTracker Sea: the technical report of BoaTrack and SeaDronesSee-MOT challenge at MaCVi of WACV24
Multi-Object Tracking is one of the most important technologies in maritime
computer vision. Our solution tries to explore Multi-Object Tracking in
maritime Unmanned Aerial vehicles (UAVs) and Unmanned Surface Vehicles (USVs)
usage scenarios. Most of the current Multi-Object Tracking algorithms require
complex association strategies and association information (2D location and
motion, 3D motion, 3D depth, 2D appearance) to achieve better performance,
which makes the entire tracking system extremely complex and heavy. At the same
time, most of the current Multi-Object Tracking algorithms still require video
annotation data which is costly to obtain for training. Our solution tries to
explore Multi-Object Tracking in a completely unsupervised way. The scheme
accomplishes instance representation learning by using self-supervision on
ImageNet. Then, by cooperating with high-quality detectors, the multi-target
tracking task can be completed simply and efficiently. The scheme achieved top
3 performance on both UAV-based Multi-Object Tracking with Reidentification and
USV-based Multi-Object Tracking benchmarks and the solution won the
championship in many multiple Multi-Object Tracking competitions. such as
BDD100K MOT,MOTS, Waymo 2D MO
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime
computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface
Vehicles (USV). Three challenges categories are considered: (i) UAV-based
Maritime Object Tracking with Re-identification, (ii) USV-based Maritime
Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking.
The USV-based Maritime Obstacle Segmentation and Detection features three
sub-challenges, including a new embedded challenge addressing efficicent
inference on real-world embedded devices. This report offers a comprehensive
overview of the findings from the challenges. We provide both statistical and
qualitative analyses, evaluating trends from over 195 submissions. All
datasets, evaluation code, and the leaderboard are available to the public at
https://macvi.org/workshop/macvi24.Comment: Part of 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 IEEE
Xplore submission as part of WACV 202
2nd Workshop on Maritime Computer Vision (MaCVi) 2024: Challenge Results
The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-Identification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficient inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi2