Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
PNAS-MOT: Multi-Modal Object Tracking with Pareto Neural Architecture Search
Multiple object tracking is a critical task in autonomous driving. Existing works primarily focus on the heuristic design of neural networks to obtain high accuracy. As tracking accuracy improves, however, neural network…
Autonomous DrivingMultiple Object TrackingNeural Architecture SearchObject+1Reasoning-Enhanced Object-Centric Learning for Videos
Object-centric learning aims to break down complex visual scenes into more manageable object representations, enhancing the understanding and reasoning abilities of machine learning systems toward the physical world. Rec…
ObjectObject TrackingCR3DT: Camera-RADAR Fusion for 3D Detection and Tracking
To enable self-driving vehicles accurate detection and tracking of surrounding objects is essential. While Light Detection and Ranging (LiDAR) sensors have set the benchmark for high-performance systems, the appeal of ca…
3D Multi-Object Tracking3D Object DetectionAutonomous DrivingMulti-Object Tracking+3Fast-Poly: A Fast Polyhedral Framework For 3D Multi-Object Tracking
3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception. However, current 3D trackers face issues with accuracy and latency consistency. I…
3D Multi-Object TrackingCPUMulti-Object TrackingObject TrackingLifting Multi-View Detection and Tracking to the Bird's Eye View
Taking advantage of multi-view aggregation presents a promising solution to tackle challenges such as occlusion and missed detection in multi-object tracking and detection. Recent advancements in multi-view detection and…
3D Object RecognitionMulti-Object Trackingmulti-view detectionMultiview Detection+2NetTrack: Tracking Highly Dynamic Objects with a Net
The complex dynamicity of open-world objects presents non-negligible challenges for multi-object tracking (MOT), often manifested as severe deformations, fast motion, and occlusions. Most methods that solely depend on co…
Multi-Object TrackingObjectObject TrackingView-Centric Multi-Object Tracking with Homographic Matching in Moving UAV
In this paper, we address the challenge of multi-object tracking (MOT) in moving Unmanned Aerial Vehicle (UAV) scenarios, where irregular flight trajectories, such as hovering, turning left/right, and moving up/down, lea…
Homography EstimationMulti-Object TrackingObjectObject TrackingMambaMOT: State-Space Model as Motion Predictor for Multi-Object Tracking
In the field of multi-object tracking (MOT), traditional methods often rely on the Kalman filter for motion prediction, leveraging its strengths in linear motion scenarios. However, the inherent limitations of these meth…
motion predictionMulti-Object TrackingMultiple Object TrackingObject TrackingNeuFlow: Real-time, High-accuracy Optical Flow Estimation on Robots Using Edge Devices
Real-time high-accuracy optical flow estimation is a crucial component in various applications, including localization and mapping in robotics, object tracking, and activity recognition in computer vision. While recent l…
Activity RecognitionEdge-computingObject TrackingOptical Flow EstimationOneTracker: Unifying Visual Object Tracking with Foundation Models and Efficient Tuning
Visual object tracking aims to localize the target object of each frame based on its initial appearance in the first frame. Depending on the input modility, tracking tasks can be divided into RGB tracking and RGB+X (e.g.…
ObjectObject TrackingRgb-T TrackingVisual Object TrackingLearning Data Association for Multi-Object Tracking using Only Coordinates
We propose a novel Transformer-based module to address the data association problem for multi-object tracking. From detections obtained by a pretrained detector, this module uses only coordinates from bounding boxes to e…
Multi-Object TrackingMultiple Object TrackingObject TrackingLong-term Frame-Event Visual Tracking: Benchmark Dataset and Baseline
Current event-/frame-event based trackers undergo evaluation on short-term tracking datasets, however, the tracking of real-world scenarios involves long-term tracking, and the performance of existing tracking algorithms…
Object TrackingRgb-T TrackingVisual TrackingSSF-Net: Spatial-Spectral Fusion Network with Spectral Angle Awareness for Hyperspectral Object Tracking
Hyperspectral video (HSV) offers valuable spatial, spectral, and temporal information simultaneously, making it highly suitable for handling challenges such as background clutter and visual similarity in object tracking.…
ObjectObject TrackingMotion-Guided Dual-Camera Tracker for Endoscope Tracking and Motion Analysis in a Mechanical Gastric Simulator
Flexible endoscope motion tracking and analysis in mechanical simulators have proven useful for endoscopy training. Common motion tracking methods based on electromagnetic tracker are however limited by their high cost a…
MambaObject TrackingPositionVisual TrackingBeyond MOT: Semantic Multi-Object Tracking
Current multi-object tracking (MOT) aims to predict trajectories of targets (i.e., ''where'') in videos. Yet, knowing merely ''where'' is insufficient in many crucial applications. In comparison, semantic understanding s…
Multi-Object TrackingObjectObject TrackingVideo UnderstandingDelving into the Trajectory Long-tail Distribution for Muti-object Tracking
Multiple Object Tracking (MOT) is a critical area within computer vision, with a broad spectrum of practical implementations. Current research has primarily focused on the development of tracking algorithms and enhanceme…
Data AugmentationMulti-Object TrackingMultiple Object TrackingObject Tracking+1VastTrack: Vast Category Visual Object Tracking
In this paper, we introduce a novel benchmark, dubbed VastTrack, towards facilitating the development of more general visual tracking via encompassing abundant classes and videos. VastTrack possesses several attractive p…
ObjectObject TrackingVisual Object TrackingVisual TrackingMulti-Object Tracking with Camera-LiDAR Fusion for Autonomous Driving
This paper presents a novel multi-modal Multi-Object Tracking (MOT) algorithm for self-driving cars that combines camera and LiDAR data. Camera frames are processed with a state-of-the-art 3D object detector, whereas cla…
Autonomous DrivingManagementMulti-Object TrackingObject+2DeconfuseTrack:Dealing with Confusion for Multi-Object Tracking
Accurate data association is crucial in reducing confusion, such as ID switches and assignment errors, in multi-object tracking (MOT). However, existing advanced methods often overlook the diversity among trajectories an…
Multi-Object TrackingObjectObject TrackingIntegrating Efficient Optimal Transport and Functional Maps For Unsupervised Shape Correspondence Learning
In the realm of computer vision and graphics, accurately establishing correspondences between geometric 3D shapes is pivotal for applications like object tracking, registration, texture transfer, and statistical shape an…
Object Trackingvalid