SOTAVerified

Pedestrian Attribute Recognition

Pedestrian attribution recognition is the task of recognizing pedestrian features - such as whether they are talking on a phone, whether they have a backpack, and so on.

( Image credit: HydraPlus-Net: Attentive Deep Features for Pedestrian Analysis )

Papers

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Showing 1–10 of 56 papers

TitleStatusHype
FOCUS: Fine-grained Optimization with Semantic Guided Understanding for Pedestrian Attributes Recognition—0
ViTA-PAR: Visual and Textual Attribute Alignment with Attribute Prompting for Pedestrian Attribute RecognitionCode0
Adversarial Semantic and Label Perturbation Attack for Pedestrian Attribute RecognitionCode0
RGB-Event based Pedestrian Attribute Recognition: A Benchmark Dataset and An Asymmetric RWKV Fusion FrameworkCode0
AttriVision: Advancing Generalization in Pedestrian Attribute Recognition using CLIP—0
Enhanced Visual-Semantic Interaction with Tailored Prompts for Pedestrian Attribute Recognition—0
SNN-PAR: Energy Efficient Pedestrian Attribute Recognition via Spiking Neural NetworksCode0
Pedestrian Attribute Recognition: A New Benchmark Dataset and A Large Language Model Augmented FrameworkCode0
An Empirical Study of Mamba-based Pedestrian Attribute RecognitionCode0
Pedestrian Attribute Recognition as Label-balanced Multi-label LearningCode1
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All datasetsPA-100KPETARAPv2RAPUAV-HumanDukeMTMC-attributeMarket1501-AttributesUPAR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AttrivisionAccuracy 83.8—Unverified