Papers Multi-Object Tracking
“Multi-Object Tracking” 태그가 달린 논문 812편 · 필터 해제
CC-3DT: Panoramic 3D Object Tracking via Cross-Camera Fusion
To track the 3D locations and trajectories of the other traffic participants at any given time, modern autonomous vehicles are equipped with multiple cameras that cover the vehicle's full surroundings. Yet, camera-based …
3D Object TrackingAutonomous VehiclesMulti-Object TrackingObject+1Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark
The evaluation of object detection models is usually performed by optimizing a single metric, e.g. mAP, on a fixed set of datasets, e.g. Microsoft COCO and Pascal VOC. Due to image retrieval and annotation costs, these d…
2D Object DetectionImage RetrievalMedical Object DetectionMulti-Object Tracking+14Hard to Track Objects with Irregular Motions and Similar Appearances? Make It Easier by Buffering the Matching Space
We propose a Cascaded Buffered IoU (C-BIoU) tracker to track multiple objects that have irregular motions and indistinguishable appearances. When appearance features are unreliable and geometric features are confused by …
Motion EstimationMulti-Object TrackingMultiple Object TrackingObject TrackingUnifying Tracking and Image-Video Object Detection
Objection detection (OD) has been one of the most fundamental tasks in computer vision. Recent developments in deep learning have pushed the performance of image OD to new heights by learning-based, data-driven approache…
Multi-Object TrackingObjectobject-detectionObject Detection+2MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors
In this paper, we propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end multi-object tracking with a pretrained object detector. Existing end-to-end methods, MOTR and TrackFormer are inferior to their t…
Multi-Object TrackingMultiple Object TrackingMultiple Object Tracking with TransformerMultiple People Tracking+2Multi-Camera Multi-Object Tracking on the Move via Single-Stage Global Association Approach
The development of autonomous vehicles generates a tremendous demand for a low-cost solution with a complete set of camera sensors capturing the environment around the car. It is essential for object detection and tracki…
3D Object DetectionAutonomous VehiclesMulti-Object TrackingObject+3Robust Online Video Instance Segmentation with Track Queries
Recently, transformer-based methods have achieved impressive results on Video Instance Segmentation (VIS). However, most of these top-performing methods run in an offline manner by processing the entire video clip at onc…
Image SegmentationInstance SegmentationMulti-Object TrackingObject Tracking+5SMILEtrack: SiMIlarity LEarning for Occlusion-Aware Multiple Object Tracking
Despite recent progress in Multiple Object Tracking (MOT), several obstacles such as occlusions, similar objects, and complex scenes remain an open challenge. Meanwhile, a systematic study of the cost-performance tradeof…
Multi-Object TrackingMultiple Object TrackingObjectobject-detection+2MEVID: Multi-view Extended Videos with Identities for Video Person Re-Identification
In this paper, we present the Multi-view Extended Videos with Identities (MEVID) dataset for large-scale, video person re-identification (ReID) in the wild. To our knowledge, MEVID represents the most-varied video person…
Multi-Object Trackingobject-detectionObject DetectionObject Tracking+3Efficient Joint Detection and Multiple Object Tracking with Spatially Aware Transformer
We propose a light-weight and highly efficient Joint Detection and Tracking pipeline for the task of Multi-Object Tracking using a fully-transformer architecture. It is a modified version of TransTrack, which overcomes t…
Multi-Object TrackingMultiple Object TrackingObject TrackingShaSTA: Modeling Shape and Spatio-Temporal Affinities for 3D Multi-Object Tracking
Multi-object tracking is a cornerstone capability of any robotic system. The quality of tracking is largely dependent on the quality of the detector used. In many applications, such as autonomous vehicles, it is preferab…
3D Multi-Object TrackingAutonomous VehiclesManagementMulti-Object Tracking+1Development and evaluation of automated localisation and reconstruction of all fruits on tomato plants in a greenhouse based on multi-view perception and 3D multi-object tracking
The ability to accurately represent and localise relevant objects is essential for robots to carry out tasks effectively. Traditional approaches, where robots simply capture an image, process that image to take an action…
3D Multi-Object TrackingAllMulti-Object TrackingObject TrackingLarge Scale Real-World Multi-Person Tracking
This paper presents a new large scale multi-person tracking dataset -- \texttt{PersonPath22}, which is over an order of magnitude larger than currently available high quality multi-object tracking datasets such as MOT17,…
Multi-Object TrackingObject TrackingThe 1st-place Solution for ECCV 2022 Multiple People Tracking in Group Dance Challenge
We present our 1st place solution to the Group Dance Multiple People Tracking Challenge. Based on MOTR: End-to-End Multiple-Object Tracking with Transformer, we explore: 1) detect queries as anchors, 2) tracking as query…
Multi-Object TrackingMultiple Object TrackingMultiple Object Tracking with TransformerMultiple People TrackingStrong-TransCenter: Improved Multi-Object Tracking based on Transformers with Dense Representations
Transformer networks have been a focus of research in many fields in recent years, being able to surpass the state-of-the-art performance in different computer vision tasks. However, in the task of Multiple Object Tracki…
Multi-Object TrackingMultiple Object TrackingMultiple Object Tracking with TransformerObject TrackingRLM-Tracking: Online Multi-Pedestrian Tracking Supported by Relative Location Mapping
The problem of multi-object tracking is a fundamental computer vision research focus, widely used in public safety, transport, autonomous vehicles, robotics, and other regions involving artificial intelligence. Because o…
Autonomous VehiclesMulti-Object TrackingObjectObject TrackingMulti-view Tracking Using Weakly Supervised Human Motion Prediction
Multi-view approaches to people-tracking have the potential to better handle occlusions than single-view ones in crowded scenes. They often rely on the tracking-by-detection paradigm, which involves detecting people firs…
Human motion predictionmotion predictionMulti-Object TrackingMultiview Detection+1RT-MOT: Confidence-Aware Real-Time Scheduling Framework for Multi-Object Tracking Tasks
Different from existing MOT (Multi-Object Tracking) techniques that usually aim at improving tracking accuracy and average FPS, real-time systems such as autonomous vehicles necessitate new requirements of MOT under limi…
Autonomous VehiclesMulti-Object TrackingObject TrackingSchedulingTrack Targets by Dense Spatio-Temporal Position Encoding
In this work, we propose a novel paradigm to encode the position of targets for target tracking in videos using transformers. The proposed paradigm, Dense Spatio-Temporal (DST) position encoding, encodes spatio-temporal …
Multi-Object TrackingMulti-Object Tracking and SegmentationObjectObject Tracking+1AttTrack: Online Deep Attention Transfer for Multi-object Tracking
Multi-object tracking (MOT) is a vital component of intelligent video analytics applications such as surveillance and autonomous driving. The time and storage complexity required to execute deep learning models for visua…
Autonomous DrivingDeep AttentionMulti-Object TrackingObject+4