Papers Multi-Object Tracking
“Multi-Object Tracking” 태그가 달린 논문 812편 · 필터 해제
Data-Model-Circuit Tri-Design for Ultra-Light Video Intelligence on Edge Devices
In this paper, we propose a data-model-hardware tri-design framework for high-throughput, low-cost, and high-accuracy multi-object tracking (MOT) on High-Definition (HD) video stream. First, to enable ultra-light video i…
Model CompressionMulti-Object TrackingObject TrackingQuo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?
Recent developments in monocular multi-object tracking have been very successful in tracking visible objects and bridging short occlusion gaps, mainly relying on data-driven appearance models. While we have significantly…
Multi-Object TrackingObject TrackingTrajectory ForecastingMultiple Object Tracking from appearance by hierarchically clustering tracklets
Current approaches in Multiple Object Tracking (MOT) rely on the spatio-temporal coherence between detections combined with object appearance to match objects from consecutive frames. In this work, we explore MOT using o…
ClusteringMulti-Object TrackingMultiple Object TrackingObject+1Interpretable Deep Tracking
Imagine experiencing a crash as the passenger of an autonomous vehicle. Wouldn't you want to know why it happened? Current end-to-end optimizable deep neural networks (DNNs) in 3D detection, multi-object tracking, and mo…
Motion ForecastingMulti-Object TrackingObject TrackingTransformers for Object Detection in Large Point Clouds
We present TransLPC, a novel detection model for large point clouds that is based on a transformer architecture. While object detection with transformers has been an active field of research, it has proved difficult to a…
Autonomous DrivingDecoderMulti-Object TrackingObject+3DirectTracker: 3D Multi-Object Tracking Using Direct Image Alignment and Photometric Bundle Adjustment
Direct methods have shown excellent performance in the applications of visual odometry and SLAM. In this work we propose to leverage their effectiveness for the task of 3D multi-object tracking. To this end, we propose D…
3D Multi-Object Tracking3D Object DetectionMulti-Object TrackingObject+4Observation Centric and Central Distance Recovery on Sports Player Tracking
Multi-Object Tracking over humans has improved rapidly with the development of object detection and re-identification. However, multi-actor tracking over humans with similar appearance and nonlinear movement can still be…
Multi-Object TrackingObjectobject-detectionObject Detection+1D$^{\bf{3}}$: Duplicate Detection Decontaminator for Multi-Athlete Tracking in Sports Videos
Tracking multiple athletes in sports videos is a very challenging Multi-Object Tracking (MOT) task, since athletes often have the same appearance and are intimately covered with each other, making a common occlusion prob…
Multi-Object TrackingObject TrackingBURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Video
Multiple existing benchmarks involve tracking and segmenting objects in video e.g., Video Object Segmentation (VOS) and Multi-Object Tracking and Segmentation (MOTS), but there is little interaction between them due to t…
Long-tail Video Object SegmentationMulti-Object TrackingMulti-Object Tracking and SegmentationObject+6Towards Frame Rate Agnostic Multi-Object Tracking
Multi-Object Tracking (MOT) is one of the most fundamental computer vision tasks that contributes to various video analysis applications. Despite the recent promising progress, current MOT research is still limited to a …
Multi-Object TrackingObjectObject TrackingPixTrack: Precise 6DoF Object Pose Tracking using NeRF Templates and Feature-metric Alignment
We present PixTrack, a vision based object pose tracking framework using novel view synthesis and deep feature-metric alignment. We follow an SfM-based relocalization paradigm where we use a Neural Radiance Field to cano…
CPUMulti-Object TrackingNeRFNovel View Synthesis+3CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion
3D Multi-object tracking (MOT) ensures consistency during continuous dynamic detection, conducive to subsequent motion planning and navigation tasks in autonomous driving. However, camera-based methods suffer in the case…
3D Multi-Object TrackingAutonomous DrivingMotion PlanningMulti-Object Tracking+2Synthehicle: Multi-Vehicle Multi-Camera Tracking in Virtual Cities
Smart City applications such as intelligent traffic routing or accident prevention rely on computer vision methods for exact vehicle localization and tracking. Due to the scarcity of accurately labeled data, detecting an…
Depth EstimationMulti-Object TrackingPanoptic SegmentationSegmentation+1Quality Matters: Embracing Quality Clues for Robust 3D Multi-Object Tracking
3D Multi-Object Tracking (MOT) has achieved tremendous achievement thanks to the rapid development of 3D object detection and 2D MOT. Recent advanced works generally employ a series of object attributes, e.g., position, …
3D Multi-Object Tracking3D Object DetectionMulti-Object TrackingObject+3Minkowski Tracker: A Sparse Spatio-Temporal R-CNN for Joint Object Detection and Tracking
Recent research in multi-task learning reveals the benefit of solving related problems in a single neural network. 3D object detection and multi-object tracking (MOT) are two heavily intertwined problems predicting and a…
3D Object DetectionMulti-Object TrackingMulti-Task LearningObject+3InterTrack: Interaction Transformer for 3D Multi-Object Tracking
3D multi-object tracking (MOT) is a key problem for autonomous vehicles, required to perform well-informed motion planning in dynamic environments. Particularly for densely occupied scenes, associating existing tracks to…
3D Multi-Object TrackingAutonomous VehiclesManagementMotion Planning+3LMOT: Efficient Light-Weight Detection and Tracking in Crowds
Multi-object tracking is a vital component in various robotics and computer vision applications. However, existing multi-object tracking techniques trade off computation runtime for tracking accuracy leading to challenge…
2D Object DetectionMulti-Object TrackingObjectObject Tracking+1Robust Multi-Object Tracking by Marginal Inference
Multi-object tracking in videos requires to solve a fundamental problem of one-to-one assignment between objects in adjacent frames. Most methods address the problem by first discarding impossible pairs whose feature dis…
Multi-Object TrackingObjectObject TrackingTransformer-based assignment decision network for multiple object tracking
Data association is a crucial component for any multiple object tracking (MOT) method that follows the tracking-by-detection paradigm. To generate complete trajectories such methods employ a data association process to e…
Multi-Object TrackingMultiple Object TrackingObject TrackingOcclusion Handling+1SOMPT22: A Surveillance Oriented Multi-Pedestrian Tracking Dataset
Multi-object tracking (MOT) has been dominated by the use of track by detection approaches due to the success of convolutional neural networks (CNNs) on detection in the last decade. As the datasets and bench-marking sit…
BenchmarkingMulti-Object TrackingObject Tracking