Person Search
48 papers with code • 2 benchmarks • 9 datasets
Person Search is a task which aims at matching a specific person among a great number of whole scene images.
Source: Re-ID Driven Localization Refinement for Person Search
Datasets
CUHK-SYSU
PRW
MovieNet
ICFG-PEDES
Market1501-Attributes
DukeMTMC-attribute
CUHK-QA
Most implemented papers
Improved Instance Discrimination and Feature Compactness for End-to-End Person Search
Vill-Lab/2021-TCSVT-IIDFC
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IEEE Transactions on Circuits and Systems for Video Technology 2021
Our method achieves comparable performance on two benchmarks, CUHK-SYSU and PRW, and achieves 91. 96% of mAP and 93. 34% of rank1 accuracy on CUHK-SYSU.
TIPCB: A Simple but Effective Part-based Convolutional Baseline for Text-based Person Search
Text-based person search is a sub-task in the field of image retrieval, which aims to retrieve target person images according to a given textual description.
APES: Audiovisual Person Search in Untrimmed Video
fuankarion/audiovisual-person-search
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To showcase the potential of our new dataset, we propose an audiovisual baseline and benchmark for person retrieval.
ASMR: Learning Attribute-Based Person Search with Adaptive Semantic Margin Regularizer
BoseungJeong/ASMR-ICCV-2021
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ICCV 2021
Attribute-based person search is the task of finding person images that are best matched with a set of text attributes given as query.
Text-based Person Search in Full Images via Semantic-Driven Proposal Generation
Finding target persons in full scene images with a query of text description has important practical applications in intelligent video surveillance. However, different from the real-world scenarios where the bounding boxes are not available, existing text-based person retrieval methods mainly focus on the cross modal matching between the query text descriptions and the gallery of cropped pedestrian images.
Text-Based Person Search with Limited Data
Firstly, to fully utilize the existing small-scale benchmarking datasets for more discriminative feature learning, we introduce a cross-modal momentum contrastive learning framework to enrich the training data for a given mini-batch.
MovieNet-PS: A Large-Scale Person Search Dataset in the Wild
Person search aims to jointly localize and identify a query person from natural, uncropped images, which has been actively studied over the past few years.
Learning Semantic-Aligned Feature Representation for Text-based Person Search
reallsp/SAF
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In this paper, we propose a semantic-aligned embedding method for text-based person search, in which the feature alignment across modalities is achieved by automatically learning the semantic-aligned visual features and textual features.
PoseTrack21: A Dataset for Person Search, Multi-Object Tracking and Multi-Person Pose Tracking
andoer/posetrack21
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CVPR 2022
Current research evaluates person search, multi-object tracking and multi-person pose estimation as separate tasks and on different datasets although these tasks are very akin to each other and comprise similar sub-tasks, e. g. person detection or appearance-based association of detected persons.
Cascade Transformers for End-to-End Person Search
In this paper, we propose the Cascade Occluded Attention Transformer (COAT) for end-to-end person search.
