Papers Object Tracking
“Object Tracking” 태그가 달린 논문 2,087편 · 필터 해제
Trashbusters: Deep Learning Approach for Litter Detection and Tracking
The illegal disposal of trash is a major public health and environmental concern. Disposing of trash in unplanned places poses serious health and environmental risks. We should try to restrict public trash cans as much a…
Deep LearningFace RecognitionObject TrackingLRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks
Visual object tracking plays a critical role in visual-based autonomous systems, as it aims to estimate the position and size of the object of interest within a live video. Despite significant progress made in this field…
ObjectObject TrackingVisual Object TrackingSelf-Supervised Multi-Object Tracking with Path Consistency
In this paper, we propose a novel concept of path consistency to learn robust object matching without using manual object identity supervision. Our key idea is that, to track a object through frames, we can obtain multip…
Multi-Object TrackingObjectObject TrackingDepthMOT: Depth Cues Lead to a Strong Multi-Object Tracker
Accurately distinguishing each object is a fundamental goal of Multi-object tracking (MOT) algorithms. However, achieving this goal still remains challenging, primarily due to: (i) For crowded scenes with occluded object…
Camera Pose EstimationMulti-Object TrackingObjectObject Tracking+1Representation Alignment Contrastive Regularization for Multi-Object Tracking
Achieving high-performance in multi-object tracking algorithms heavily relies on modeling spatio-temporal relationships during the data association stage. Mainstream approaches encompass rule-based and deep learning-base…
Multi-Object TrackingObjectObject TrackingEgo-Motion Aware Target Prediction Module for Robust Multi-Object Tracking
Multi-object tracking (MOT) is a prominent task in computer vision with application in autonomous driving, responsible for the simultaneous tracking of multiple object trajectories. Detection-based multi-object tracking …
Autonomous DrivingMulti-Object TrackingObjectObject TrackingMTMMC: A Large-Scale Real-World Multi-Modal Camera Tracking Benchmark
Multi-target multi-camera tracking is a crucial task that involves identifying and tracking individuals over time using video streams from multiple cameras. This task has practical applications in various fields, such as…
Anomaly DetectionHuman DetectionMultiple Object TrackingObject TrackingSceneTracker: Long-term Scene Flow Estimation Network
Considering the complementarity of scene flow estimation in the spatial domain's focusing capability and 3D object tracking in the temporal domain's coherence, this study aims to address a comprehensive new task that can…
3D Object TrackingObject TrackingScene Flow EstimationBayesian Nonparametrics: An Alternative to Deep Learning
Bayesian nonparametric models offer a flexible and powerful framework for statistical model selection, enabling the adaptation of model complexity to the intricacies of diverse datasets. This survey intends to delve into…
Deep LearningElectrical EngineeringModel SelectionMulti-Object Tracking+2TAFormer: A Unified Target-Aware Transformer for Video and Motion Joint Prediction in Aerial Scenes
As drone technology advances, using unmanned aerial vehicles for aerial surveys has become the dominant trend in modern low-altitude remote sensing. The surge in aerial video data necessitates accurate prediction for fut…
Disaster ResponseObject TrackingPredictionVideo PredictionMiddle Fusion and Multi-Stage, Multi-Form Prompts for Robust RGB-T Tracking
RGB-T tracking, a vital downstream task of object tracking, has made remarkable progress in recent years. Yet, it remains hindered by two major challenges: 1) the trade-off between performance and efficiency; 2) the scar…
FormObject TrackingPrompt LearningRgb-T TrackingEnhancing Multiple Object Tracking Accuracy via Quantum Annealing
Multiple object tracking (MOT), a key task in image recognition, presents a persistent challenge in balancing processing speed and tracking accuracy. This study introduces a novel approach that leverages quantum annealin…
ManagementMultiple Object TrackingObjectObject TrackingOmniVid: A Generative Framework for Universal Video Understanding
The core of video understanding tasks, such as recognition, captioning, and tracking, is to automatically detect objects or actions in a video and analyze their temporal evolution. Despite sharing a common goal, differen…
Action RecognitionDecoderDense Video CaptioningObject Tracking+5Exploring Dynamic Transformer for Efficient Object Tracking
The speed-precision trade-off is a critical problem for visual object tracking which usually requires low latency and deployment on constrained resources. Existing solutions for efficient tracking mainly focus on adoptin…
ObjectObject TrackingVisual Object TrackingMultiple Object Tracking as ID Prediction
In Multiple Object Tracking (MOT), tracking-by-detection methods have stood the test for a long time, which split the process into two parts according to the definition: object detection and association. They leverage ro…
Multi-Object TrackingMultiple Object TrackingObjectobject-detection+3Elysium: Exploring Object-level Perception in Videos via MLLM
Multi-modal Large Language Models (MLLMs) have demonstrated their ability to perceive objects in still images, but their application in video-related tasks, such as object tracking, remains understudied. This lack of exp…
ObjectObject TrackingReferring ExpressionReferring Expression Comprehension+5Spike-NeRF: Neural Radiance Field Based On Spike Camera
As a neuromorphic sensor with high temporal resolution, spike cameras offer notable advantages over traditional cameras in high-speed vision applications such as high-speed optical estimation, depth estimation, and objec…
3D ReconstructionDepth EstimationNeRFObject TrackingFrom Two-Stream to One-Stream: Efficient RGB-T Tracking via Mutual Prompt Learning and Knowledge Distillation
Due to the complementary nature of visible light and thermal infrared modalities, object tracking based on the fusion of visible light images and thermal images (referred to as RGB-T tracking) has received increasing att…
Knowledge DistillationObject TrackingPrompt LearningRgb-T TrackingSDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking
Multimodal Visual Object Tracking (VOT) has recently gained significant attention due to its robustness. Early research focused on fully fine-tuning RGB-based trackers, which was inefficient and lacked generalized repres…
Object TrackingRgb-T TrackingVisual Object TrackingSpatio-Temporal Bi-directional Cross-frame Memory for Distractor Filtering Point Cloud Single Object Tracking
3D single object tracking within LIDAR point clouds is a pivotal task in computer vision, with profound implications for autonomous driving and robotics. However, existing methods, which depend solely on appearance match…
3D Single Object TrackingAutonomous DrivingObject LocalizationObject Tracking