Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
XTrack: Multimodal Training Boosts RGB-X Video Object Trackers
Multimodal sensing has proven valuable for visual tracking, as different sensor types offer unique strengths in handling one specific challenging scene where object appearance varies. While a generalist model capable of …
Inductive BiasMixture-of-ExpertsMulti-Label ClassificationObject Tracking+3Track Initialization and Re-Identification for~3D Multi-View Multi-Object Tracking
We propose a 3D multi-object tracking (MOT) solution using only 2D detections from monocular cameras, which automatically initiates/terminates tracks as well as resolves track appearance-reappearance and occlusions. More…
3D Multi-Object TrackingMulti-Object TrackingObjectObject Tracking+1Tracking Small Birds by Detection Candidate Region Filtering and Detection History-aware Association
This paper focuses on tracking birds that appear small in a panoramic video. When the size of the tracked object is small in the image (small object tracking) and move quickly, object detection and association suffers. T…
Objectobject-detectionObject DetectionObject TrackingBaboonLand Dataset: Tracking Primates in the Wild and Automating Behaviour Recognition from Drone Videos
Using drones to track multiple individuals simultaneously in their natural environment is a powerful approach for better understanding group primate behavior. Previous studies have demonstrated that it is possible to aut…
Animal Action RecognitionMultiple Object TrackingObject TrackingAn Approximate Dynamic Programming Framework for Occlusion-Robust Multi-Object Tracking
In this work, we consider data association problems involving multi-object tracking (MOT). In particular, we address the challenges arising from object occlusions. We propose a framework called approximate dynamic progra…
Multi-Object TrackingObject TrackingETTrack: Enhanced Temporal Motion Predictor for Multi-Object Tracking
Many Multi-Object Tracking (MOT) approaches exploit motion information to associate all the detected objects across frames. However, many methods that rely on filtering-based algorithms, such as the Kalman Filter, often …
Multi-Object TrackingObject TrackingTrackastra: Transformer-based cell tracking for live-cell microscopy
Cell tracking is a ubiquitous image analysis task in live-cell microscopy. Unlike multiple object tracking (MOT) for natural images, cell tracking typically involves hundreds of similar-looking objects that can divide in…
Cell TrackingMultiple Object TrackingObject TrackingAwesome Multi-modal Object Tracking
Multi-modal object tracking (MMOT) is an emerging field that combines data from various modalities, \eg vision (RGB), depth, thermal infrared, event, language and audio, to estimate the state of an arbitrary object in a …
Autonomous DrivingKnowledge DistillationMiscellaneousObject+5Enhanced Object Tracking by Self-Supervised Auxiliary Depth Estimation Learning
RGB-D tracking significantly improves the accuracy of object tracking. However, its dependency on real depth inputs and the complexity involved in multi-modal fusion limit its applicability across various scenarios. The …
Depth EstimationMonocular Depth EstimationObject TrackingPuTR: A Pure Transformer for Decoupled and Online Multi-Object Tracking
Recent advances in Multi-Object Tracking (MOT) have achieved remarkable success in short-term association within the decoupled tracking-by-detection online paradigm. However, long-term tracking still remains a challengin…
Multi-Object TrackingObjectObject TrackingOnline Multi-Object TrackingMulti Player Tracking in Ice Hockey with Homographic Projections
Multi Object Tracking (MOT) in ice hockey pursues the combined task of localizing and associating players across a given sequence to maintain their identities. Tracking players from monocular broadcast feeds is an import…
Graph MatchingMulti-Object TrackingObject TrackingDTLLM-VLT: Diverse Text Generation for Visual Language Tracking Based on LLM
Visual Language Tracking (VLT) enhances single object tracking (SOT) by integrating natural language descriptions from a video, for the precise tracking of a specified object. By leveraging high-level semantic informatio…
Object TrackingText GenerationVisual TrackingTrack Anything Rapter(TAR)
Object tracking is a fundamental task in computer vision with broad practical applications across various domains, including traffic monitoring, robotics, and autonomous vehicle tracking. In this project, we aim to devel…
Motion PlanningObjectObject TrackingTARRobMOT: Robust 3D Multi-Object Tracking by Observational Noise and State Estimation Drift Mitigation on LiDAR PointCloud
This paper addresses limitations in 3D tracking-by-detection methods, particularly in identifying legitimate trajectories and reducing state estimation drift in Kalman filters. Existing methods often use threshold-based …
3D Multi-Object TrackingCPUMulti-Object TrackingMultiple Object Tracking+3Air Signing and Privacy-Preserving Signature Verification for Digital Documents
This paper presents a novel approach to the digital signing of electronic documents through the use of a camera-based interaction system, single-finger tracking for sign recognition, and multi commands executing hand ges…
Fingertip DetectionGesture RecognitionObject TrackingPrivacy PreservingSpatial Cognition: a Wave Hypothesis
Animals build Bayesian 3D models of their surroundings, to control their movements. There is strong selection pressure to make these models as precise as possible, given their sense data. A previous paper has described h…
Object TrackingA Novel Bounding Box Regression Method for Single Object Tracking
Locating an object in a sequence of frames, given its appearance in the first frame of the sequence, is a hard problem that involves many stages. Usually, state-of-the-art methods focus on bringing novel ideas in the vis…
Object TrackingregressionBeyond Traditional Single Object Tracking: A Survey
Single object tracking is a vital task of many applications in critical fields. However, it is still considered one of the most challenging vision tasks. In recent years, computer vision, especially object tracking, witn…
Continual LearningDomain AdaptationMeta-LearningObject+3Learning Correspondence for Deformable Objects
We investigate the problem of pixelwise correspondence for deformable objects, namely cloth and rope, by comparing both classical and learning-based methods. We choose cloth and rope because they are traditionally some o…
ObjectObject TrackingADA-Track++: End-to-End Multi-Camera 3D Multi-Object Tracking with Alternating Detection and Association
Many query-based approaches for 3D Multi-Object Tracking (MOT) adopt the tracking-by-attention paradigm, utilizing track queries for identity-consistent detection and object queries for identity-agnostic track spawning. …
3D Multi-Object TrackingDecoderMulti-Object TrackingObject Tracking