Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
Visual SLAMMOT Considering Multiple Motion Models
Simultaneous Localization and Mapping (SLAM) and Multi-Object Tracking (MOT) are pivotal tasks in the realm of autonomous driving, attracting considerable research attention. While SLAM endeavors to generate real-time ma…
Autonomous DrivingMulti-Object TrackingObject TrackingSimultaneous Localization and MappingCrossTracker: Robust Multi-modal 3D Multi-Object Tracking via Cross Correction
The fusion of camera- and LiDAR-based detections offers a promising solution to mitigate tracking failures in 3D multi-object tracking (MOT). However, existing methods predominantly exploit camera detections to correct t…
3D Multi-Object TrackingMulti-Object TrackingObject TrackingA comparison of extended object tracking with multi-modal sensors in indoor environment
This paper presents a preliminary study of an efficient object tracking approach, comparing the performance of two different 3D point cloud sensory sources: LiDAR and stereo cameras, which have significant price differen…
ObjectObject TrackingA Distractor-Aware Memory for Visual Object Tracking with SAM2
Memory-based trackers are video object segmentation methods that form the target model by concatenating recently tracked frames into a memory buffer and localize the target by attending the current image to the buffered …
Object TrackingSemi-Supervised Video Object SegmentationVisual Object TrackingVisual TrackingFastTrackTr:Towards Fast Multi-Object Tracking with Transformers
Transformer-based multi-object tracking (MOT) methods have captured the attention of many researchers in recent years. However, these models often suffer from slow inference speeds due to their structure or other issues.…
Multi-Object TrackingObjectObject TrackingMambaTrack: Exploiting Dual-Enhancement for Night UAV Tracking
Night unmanned aerial vehicle (UAV) tracking is impeded by the challenges of poor illumination, with previous daylight-optimized methods demonstrating suboptimal performance in low-light conditions, limiting the utility …
GPUImage EnhancementMambaObject TrackingHow Texts Help? A Fine-grained Evaluation to Reveal the Role of Language in Vision-Language Tracking
Vision-language tracking (VLT) extends traditional single object tracking by incorporating textual information, providing semantic guidance to enhance tracking performance under challenging conditions like fast motion an…
Object TrackingMambaVLT: Time-Evolving Multimodal State Space Model for Vision-Language Tracking
The vision-language tracking task aims to perform object tracking based on various modality references. Existing Transformer-based vision-language tracking methods have made remarkable progress by leveraging the global m…
MambaObject TrackingEnhancing Thermal MOT: A Novel Box Association Method Leveraging Thermal Identity and Motion Similarity
Multiple Object Tracking (MOT) in thermal imaging presents unique challenges due to the lack of visual features and the complexity of motion patterns. This paper introduces an innovative approach to improve MOT in the th…
Multiple Object TrackingObjectObject TrackingTeaching VLMs to Localize Specific Objects from In-context Examples
Vision-Language Models (VLMs) have shown remarkable capabilities across diverse visual tasks, including image recognition, video understanding, and Visual Question Answering (VQA) when explicitly trained for these tasks.…
ObjectObject TrackingQuestion AnsweringVideo Object Tracking+3ClickTrack: Towards Real-time Interactive Single Object Tracking
Single object tracking(SOT) relies on precise object bounding box initialization. In this paper, we reconsidered the deficiencies in the current approaches to initializing single object trackers and propose a new paradig…
ObjectObject TrackingSemantic SegmentationVideo Object Segmentation+1Improved Estimation Accuracy in OFDM-based Joint Communication and Sensing through Kalman Tracking and Interpolation
We investigate a monostatic orthogonal frequency-division multiplexing (OFDM)-based joint communication and sensing (JCAS) system for object tracking. Our setup consists of a transmitter and receiver equipped with an ant…
Object TrackingLearning a Neural Association Network for Self-supervised Multi-Object Tracking
This paper introduces a novel framework to learn data association for multi-object tracking in a self-supervised manner. Fully-supervised learning methods are known to achieve excellent tracking performances, but acquiri…
Multi-Object TrackingObject TrackingSAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory
The Segment Anything Model 2 (SAM 2) has demonstrated strong performance in object segmentation tasks but faces challenges in visual object tracking, particularly when managing crowded scenes with fast-moving or self-occ…
Object TrackingVisual Object TrackingVisual TrackingReal-Time AI-Driven People Tracking and Counting Using Overhead Cameras
Accurate people counting in smart buildings and intelligent transportation systems is crucial for energy management, safety protocols, and resource allocation. This is especially critical during emergencies, where precis…
energy managementManagementObjectobject-detection+2MOT FCG++: Enhanced Representation of Spatio-temporal Motion and Appearance Features
The goal of multi-object tracking (MOT) is to detect and track all objects in a scene across frames, while maintaining a unique identity for each object. Most existing methods rely on the spatial-temporal motion features…
Multi-Object TrackingObject TrackingState Estimation3D Multi-Object Tracking with Semi-Supervised GRU-Kalman Filter
3D Multi-Object Tracking (MOT), a fundamental component of environmental perception, is essential for intelligent systems like autonomous driving and robotic sensing. Although Tracking-by-Detection frameworks have demons…
3D Multi-Object TrackingAutonomous DrivingMulti-Object TrackingObject+1DEEGITS: Deep Learning based Framework for Measuring Heterogenous Traffic State in Challenging Traffic Scenarios
This paper presents DEEGITS (Deep Learning Based Heterogeneous Traffic State Measurement), a comprehensive framework that leverages state-of-the-art convolutional neural network (CNN) techniques to accurately and rapidly…
Multi-Object TrackingObject TrackingTransfer LearningGTA: Global Tracklet Association for Multi-Object Tracking in Sports
Multi-object tracking in sports scenarios has become one of the focal points in computer vision, experiencing significant advancements through the integration of deep learning techniques. Despite these breakthroughs, cha…
Multi-Object TrackingMultiple Object TrackingObject TrackingBuckTales : A multi-UAV dataset for multi-object tracking and re-identification of wild antelopes
Understanding animal behaviour is central to predicting, understanding, and mitigating impacts of natural and anthropogenic changes on animal populations and ecosystems. However, the challenges of acquiring and processin…
BenchmarkingMulti-Object TrackingObject Tracking