Person Retrieval
25 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Person Retrieval
| Trend | Dataset | Best Model | Paper | Code | Compare |
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RSTPReid
ITCPR dataset
Most implemented papers
Part-based Pseudo Label Refinement for Unsupervised Person Re-identification
In this paper, we propose a novel Part-based Pseudo Label Refinement (PPLR) framework that reduces the label noise by employing the complementary relationship between global and part features.
Cross-Camera Trajectories Help Person Retrieval in a Camera Network
zhangxin1995/PTD
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To address this issue, we propose a pedestrian retrieval framework based on cross-camera trajectory generation, which integrates both temporal and spatial information.
See Finer, See More: Implicit Modality Alignment for Text-based Person Retrieval
tencentyouturesearch/personretrieval-ivt
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To explore the fine-grained alignment, we further propose two implicit semantic alignment paradigms: multi-level alignment (MLA) and bidirectional mask modeling (BMM).
UPAR: Unified Pedestrian Attribute Recognition and Person Retrieval
It is based on four well-known person attribute recognition datasets: PA100K, PETA, RAPv2, and Market1501.
Co-Attention Aligned Mutual Cross-Attention for Cloth-Changing Person Re-Identification
QizaoWang/CAMC-CCReID
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Asian Conference on Computer Vision (ACCV) 2023
In this paper, we first design a novel Shape Semantics Embedding (SSE) module to encode body shape semantic information, which is one of the essential clues to distinguish pedestrians when their clothes change.
Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval
To alleviate these issues, we present IRRA: a cross-modal Implicit Relation Reasoning and Aligning framework that learns relations between local visual-textual tokens and enhances global image-text matching without requiring additional prior supervision.
Towards Unified Text-based Person Retrieval: A Large-scale Multi-Attribute and Language Search Benchmark
Shuyu-XJTU/APTM
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To verify the feasibility of learning from the generated data, we develop a new joint Attribute Prompt Learning and Text Matching Learning (APTM) framework, considering the shared knowledge between attribute and text.
Lightweight Attribute Localizing Models for Pedestrian Attribute Recognition
ashishjv1/LW-ALM
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Pedestrian Attribute Recognition (PAR) deals with the problem of identifying features in a pedestrian image.
Beyond Domain Gap: Exploiting Subjectivity in Sketch-Based Person Retrieval
lin-kayla/subjectivity-sketch-reid
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2) Multi-perspective and multi-style.
CA-Jaccard: Camera-aware Jaccard Distance for Person Re-identification
In particular, Jaccard distance calculates the distance based on the overlap of relevant neighbors.
