Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
3D Extended Object Tracking based on Extruded B-Spline Side View Profiles
Object tracking is an essential task for autonomous systems. With the advancement of 3D sensors, these systems can better perceive their surroundings using effective 3D Extended Object Tracking (EOT) methods. Based on th…
ObjectObject TrackingHow good are deep learning methods for automated road safety analysis using video data? An experimental study
Image-based multi-object detection (MOD) and multi-object tracking (MOT) are advancing at a fast pace. A variety of 2D and 3D MOD and MOT methods have been developed for monocular and stereo cameras. Road safety analysis…
Multi-Object Trackingobject-detectionObject DetectionObject TrackingTrackOcc: Camera-based 4D Panoptic Occupancy Tracking
Comprehensive and consistent dynamic scene understanding from camera input is essential for advanced autonomous systems. Traditional camera-based perception tasks like 3D object tracking and semantic occupancy prediction…
3D Object TrackingObject TrackingScene UnderstandingJust Functioning as a Hook for Two-Stage Referring Multi-Object Tracking
Referring Multi-Object Tracking (RMOT) aims to localize target trajectories specified by natural language expressions in videos. Existing RMOT methods mainly follow two paradigms: one-stage strategies and two-stage ones.…
Computational EfficiencyContrastive LearningMulti-Object TrackingObject Tracking+1Omnidirectional Multi-Object Tracking
Panoramic imagery, with its 360{\deg} field of view, offers comprehensive information to support Multi-Object Tracking (MOT) in capturing spatial and temporal relationships of surrounding objects. However, most MOT algor…
Multi-Object TrackingObjectObject LocalizationObject TrackingReynoldsFlow: Exquisite Flow Estimation via Reynolds Transport Theorem
Optical flow is a fundamental technique for motion estimation, widely applied in video stabilization, interpolation, and object tracking. Traditional optical flow estimation methods rely on restrictive assumptions like b…
Motion EstimationObjectobject-detectionObject Detection+4A Modular Pipeline for 3D Object Tracking Using RGB Cameras
Object tracking is a key challenge of computer vision with various applications that all require different architectures. Most tracking systems have limitations such as constraining all movement to a 2D plane and they of…
3D Object TrackingObject TrackingAI-Driven Relocation Tracking in Dynamic Kitchen Environments
As smart homes become more prevalent in daily life, the ability to understand dynamic environments is essential which is increasingly dependent on AI systems. This study focuses on developing an intelligent algorithm whi…
2D Object Detection3D ReconstructionIndoor LocalizationNavigate+3MITracker: Multi-View Integration for Visual Object Tracking
Multi-view object tracking (MVOT) offers promising solutions to challenges such as occlusion and target loss, which are common in traditional single-view tracking. However, progress has been limited by the lack of compre…
ObjectObject TrackingVisual Object TrackingSpectral-Enhanced Transformers: Leveraging Large-Scale Pretrained Models for Hyperspectral Object Tracking
Hyperspectral object tracking using snapshot mosaic cameras is emerging as it provides enhanced spectral information alongside spatial data, contributing to a more comprehensive understanding of material properties. Usin…
ObjectObject TrackingEasy-Poly: A Easy Polyhedral Framework For 3D Multi-Object Tracking
Recent advancements in 3D multi-object tracking (3D MOT) have predominantly relied on tracking-by-detection pipelines. However, these approaches often neglect potential enhancements in 3D detection processes, leading to …
3D Multi-Object TrackingAutonomous DrivingData AugmentationManagement+2UASTrack: A Unified Adaptive Selection Framework with Modality-Customization in Single Object Tracking
Multi-modal tracking is essential in single-object tracking (SOT), as different sensor types contribute unique capabilities to overcome challenges caused by variations in object appearance. However, existing unified RGB-…
Object TrackingCRTrack: Low-Light Semi-Supervised Multi-object Tracking Based on Consistency Regularization
Multi-object tracking under low-light environments is prevalent in real life. Recent years have seen rapid development in the field of multi-object tracking. However, due to the lack of datasets and the high cost of anno…
Multi-Object TrackingObjectObject TrackingV-HOP: Visuo-Haptic 6D Object Pose Tracking
Humans naturally integrate vision and haptics for robust object perception during manipulation. The loss of either modality significantly degrades performance. Inspired by this multisensory integration, prior object pose…
ObjectObject TrackingPose EstimationPose TrackingBenchmarking Online Object Trackers for Underwater Robot Position Locking Applications
Autonomously controlling the position of Remotely Operated underwater Vehicles (ROVs) is of crucial importance for a wide range of underwater engineering applications, such as in the inspection and maintenance of underwa…
BenchmarkingObject TrackingPositionRobot NavigationMEX: Memory-efficient Approach to Referring Multi-Object Tracking
Referring Multi-Object Tracking (RMOT) is a relatively new concept that has rapidly gained traction as a promising research direction at the intersection of computer vision and natural language processing. Unlike traditi…
Autonomous DrivingGPUMulti-Object TrackingObject+2IMM-MOT: A Novel 3D Multi-object Tracking Framework with Interacting Multiple Model Filter
3D Multi-Object Tracking (MOT) provides the trajectories of surrounding objects, assisting robots or vehicles in smarter path planning and obstacle avoidance. Existing 3D MOT methods based on the Tracking-by-Detection fr…
3D Multi-Object TrackingMulti-Object TrackingObject TrackingAdaptive Perception for Unified Visual Multi-modal Object Tracking
Recently, many multi-modal trackers prioritize RGB as the dominant modality, treating other modalities as auxiliary, and fine-tuning separately various multi-modal tasks. This imbalance in modality dependence limits the …
Object TrackingRgb-T TrackingEvent Stream-based Visual Object Tracking: HDETrack V2 and A High-Definition Benchmark
We then introduce a novel hierarchical knowledge distillation strategy that incorporates the similarity matrix, feature representation, and response map-based distillation to guide the learning of the student Transformer…
Knowledge DistillationObject TrackingVisual Object TrackingOneTrack-M: A multitask approach to transformer-based MOT models
Multi-Object Tracking (MOT) is a critical problem in computer vision, essential for understanding how objects move and interact in videos. This field faces significant challenges such as occlusions and complex environmen…
Autonomous VehiclesComputational EfficiencyDecoderMulti-Object Tracking+3