A comprehensive survey on segment anything model for vision and beyond
Artificial intelligence (AI) is evolving towards artificial general intelligence, which refers to the
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …
ability of an AI system to perform a wide range of tasks and exhibit a level of intelligence …
Radars for autonomous driving: A review of deep learning methods and challenges
A Srivastav, S Mandal - IEEE Access, 2023 - ieeexplore.ieee.org
Radar is a key component of the suite of perception sensors used for safe and reliable
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
CY Wang, A Bochkovskiy… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
Real-time object detection is one of the most important research topics in computer vision.
As new approaches regarding architecture optimization and training optimization are …
As new approaches regarding architecture optimization and training optimization are …
Strongsort: Make deepsort great again
Y Du, Z Zhao, Y Song, Y Zhao, F Su… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Recently, Multi-Object Tracking (MOT) has attracted rising attention, and accordingly,
remarkable progresses have been achieved. However, the existing methods tend to use …
remarkable progresses have been achieved. However, the existing methods tend to use …
Universal instance perception as object discovery and retrieval
All instance perception tasks aim at finding certain objects specified by some queries such
as category names, language expressions, and target annotations, but this complete field …
as category names, language expressions, and target annotations, but this complete field …
BoT-SORT: Robust associations multi-pedestrian tracking
N Aharon, R Orfaig, BZ Bobrovsky - arXiv preprint arXiv:2206.14651, 2022 - arxiv.org
The goal of multi-object tracking (MOT) is detecting and tracking all the objects in a scene,
while keeping a unique identifier for each object. In this paper, we present a new robust …
while keeping a unique identifier for each object. In this paper, we present a new robust …
Aiatrack: Attention in attention for transformer visual tracking
Transformer trackers have achieved impressive advancements recently, where the attention
mechanism plays an important role. However, the independent correlation computation in …
mechanism plays an important role. However, the independent correlation computation in …
Exploring object-centric temporal modeling for efficient multi-view 3d object detection
In this paper, we propose a long-sequence modeling framework, named StreamPETR, for
multi-view 3D object detection. Built upon the sparse query design in the PETR series, we …
multi-view 3D object detection. Built upon the sparse query design in the PETR series, we …
Motr: End-to-end multiple-object tracking with transformer
Temporal modeling of objects is a key challenge in multiple-object tracking (MOT). Existing
methods track by associating detections through motion-based and appearance-based …
methods track by associating detections through motion-based and appearance-based …
Towards grand unification of object tracking
We present a unified method, termed Unicorn, that can simultaneously solve four tracking
problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters …
problems (SOT, MOT, VOS, MOTS) with a single network using the same model parameters …