Object tracking is the task of taking an initial set of object detections, creating a unique ID for each of the initial detections, and then tracking each of the objects as they move around frames in a video, maintaining the ID assignment.
( Image credit: Towards-Realtime-MOT )
In this paper we illustrate how to perform both visual object tracking and semi-supervised video object segmentation, in real-time, with a single simple approach.
#3 best model for Visual Object Tracking on YouTube-VOS
Simple Online and Realtime Tracking (SORT) is a pragmatic approach to multiple object tracking with a focus on simple, effective algorithms.
During the off-line training phase, an effective sampling strategy is introduced to control this distribution and make the model focus on the semantic distractors.
#9 best model for Visual Object Tracking on VOT2017/18
Visual object tracking has been a fundamental topic in recent years and many deep learning based trackers have achieved state-of-the-art performance on multiple benchmarks.
#5 best model for Visual Object Tracking on VOT2017/18
This paper addresses the problem of estimating and tracking human body keypoints in complex, multi-person video.
#5 best model for Pose Tracking on PoseTrack2017 (using extra training data)
In this paper, we propose an MOT system that allows target detection and appearance embedding to be learned in a shared model.
SOTA for Multi-Object Tracking on MOT16 (using extra training data)
To the best of our knowledge, this is the first paper to propose an online human pose tracking framework in a top-down fashion.
#2 best model for Pose Tracking on PoseTrack2017 (using extra training data)