Results 31 to 40 of about 4,392,511 (325)
Referring Multi-Object Tracking [PDF]
Computer Vision and Pattern Recognition, 2023 Existing referring understanding tasks tend to involve the detection of a single text-referred object. In this paper, we propose a new and general referring understanding task, termed referring multi-object tracking (RMOT).
Dongming Wu +5 more
semanticscholar +1 more source
MeMOTR: Long-Term Memory-Augmented Transformer for Multi-Object Tracking [PDF]
IEEE International Conference on Computer Vision, 2023 As a video task, Multiple Object Tracking (MOT) is expected to capture temporal information of targets effectively. Unfortunately, most existing methods only explicitly exploit the object features between adjacent frames, while lacking the capacity to ...
Ruopeng Gao, Limin Wang
semanticscholar +1 more source
A New Object Tracking Framework for Interest Point Based Feature Extraction Algorithms
Elektronika ir Elektrotechnika, 2020 This paper presents a novel object tracking framework for interest point based feature extracting algorithms. The proposed framework uses the feature extracting algorithm without making any changes and it relies on outlier detection, object modelling ...
Zafer Guler, Ahmet Cinar, Erdal Ozbay
doaj +1 more source
Single-Model and Any-Modality for Video Object Tracking [PDF]
Computer Vision and Pattern Recognition, 2023 In the realm of video object tracking, auxiliary modalities such as depth, thermal, or event data have emerged as valuable assets to complement the RGB trackers.
Zongwei Wu +7 more
semanticscholar +1 more source
Object-Centric Multiple Object Tracking
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 ICCV 2023 camera-ready ...
Zhao, Z. +15 more
openaire +3 more sources
Standing Between Past and Future: Spatio-Temporal Modeling for Multi-Camera 3D Multi-Object Tracking [PDF]
Computer Vision and Pattern Recognition, 2023 This work proposes an end-to-end multi-camera 3D multi-object tracking (MOT) framework. It emphasizes spatio-temporal continuity and integrates both past and future reasoning for tracked objects. Thus, we name it “Past- and-Future reasoning for Tracking”
Ziqi Pang +5 more
semanticscholar +1 more source
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search [PDF]
Computer Vision and Pattern Recognition, 2021 Object tracking has achieved significant progress over the past few years. However, state-of-the-art trackers become increasingly heavy and expensive, which limits their deployments in resource-constrained applications.
B. Yan +5 more
semanticscholar +1 more source
MeMOT: Multi-Object Tracking with Memory [PDF]
Computer Vision and Pattern Recognition, 2022 We propose an online tracking algorithm that performs the object detection and data association under a common framework, capable of linking objects after a long time span.
Jiarui Cai +6 more
semanticscholar +1 more source
Multi-Object Tracking on SWIR Images for City Surveillance in an Edge-Computing Environment
Sensors, 2023 Although Short-Wave Infrared (SWIR) sensors have advantages in terms of robustness in bad weather and low-light conditions, the SWIR images have not been well studied for automated object detection and tracking systems.
Jihun Park +3 more
doaj +1 more source
Manifold Regularized Correlation Object Tracking [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2018 In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples.
Hongwei Hu +3 more
openaire +4 more sources