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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 26–50 of 56 papers

TitleStatusHype
POAR: Towards Open Vocabulary Pedestrian Attribute RecognitionCode0
HumanBench: Towards General Human-centric Perception with Projector Assisted PretrainingCode2
UniHCP: A Unified Model for Human-Centric PerceptionsCode1
Image-Based and Partially Categorical Annotating Approach for Pedestrian Attribute RecognitionCode1
Learning Disentangled Label Representations for Multi-label Classification—0
UPAR: Unified Pedestrian Attribute Recognition and Person RetrievalCode1
Label2Label: A Language Modeling Framework for Multi-Attribute LearningCode1
Reinforced Pedestrian Attribute Recognition with Group Optimization Reward—0
Robust Pedestrian Attribute Recognition Using Group Sparsity for Occlusion Videos—0
Spatial and Semantic Consistency Regularizations for Pedestrian Attribute Recognition—0
YinYang-Net: Complementing Face and Body Information for Wild Gender RecognitionCode0
Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity SettingCode1
Pedestrian Attribute Recognition in Video Surveillance Scenarios Based on View-attribute Attention Localization—0
UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial VehiclesCode1
Deep Template Matching for Pedestrian Attribute Recognition with the Auxiliary Supervision of Attribute-wise Keypoints—0
Identity-Aware Attribute Recognition via Real-Time Distributed Inference in Mobile Edge Clouds—0
Rethinking of Pedestrian Attribute Recognition: Realistic Datasets with Efficient MethodCode1
Data Augmentation Imbalance For Imbalanced Attribute Classification—0
Multi-Task Learning via Co-Attentive Sharing for Pedestrian Attribute Recognition—0
Improving Pedestrian Attribute Recognition With Weakly-Supervised Multi-Scale Attribute-Specific LocalizationCode1
Unsupervised Domain-Adaptive Person Re-identification Based on Attributes—0
Attribute Aware Pooling for Pedestrian Attribute Recognition—0
Incremental Few-Shot Learning for Pedestrian Attribute Recognition—0
Pedestrian Attribute Recognition: A SurveyCode0
A Temporal Attentive Approach for Video-Based Pedestrian Attribute Recognition—0
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All datasetsPA-100KPETARAPv2RAPUAV-HumanDukeMTMC-attributeMarket1501-AttributesUPAR

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AttivisionF1 score93.1—Unverified
2PATH (Partial FT)Accuracy90.8—Unverified
3AttrivisionAccuracy 89.8—Unverified
4Hulk(Finetune, ViT-L)Accuracy88.97—Unverified
5Hulk(Finetune, ViT-B)Accuracy87.85—Unverified
6C2T-NetAccuracy87.2—Unverified
7SOLIDERAccuracy86.38—Unverified
8UniHCP (finetune)Accuracy86.18—Unverified
9APTMAccuracy80.17—Unverified
10Label2LabelAccuracy79.23—Unverified
#ModelMetricClaimedVerifiedStatus
1UniHCP (FT)Accuracy88.78—Unverified
2C2T-NetAccuracy88.2—Unverified
3ALM[tang2019Improving] (ICCV19)Accuracy79.52—Unverified
4Attribute-Specific LocalizationAccuracy79.52—Unverified
5strongbaselineAccuracy79.14—Unverified
6HP-netAccuracy76.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Hulk(Finetune, ViT-L)Accuracy85.86—Unverified
2Hulk(Finetune, ViT-B)Accuracy85.26—Unverified
3AttrivisionAccuracy 84.2—Unverified
4UniHCP (finetune)Accuracy82.34—Unverified
#ModelMetricClaimedVerifiedStatus
1Attribute-Specific LocalizationAccuracy68.17—Unverified
2HP-netAccuracy65.39—Unverified
#ModelMetricClaimedVerifiedStatus
1DenseNetBackpack63.9—Unverified
2ResNetBackpack63.5—Unverified
#ModelMetricClaimedVerifiedStatus
1MBNETAccuracy91.13—Unverified
#ModelMetricClaimedVerifiedStatus
1AttrivisionAccuracy 83.8—Unverified
#ModelMetricClaimedVerifiedStatus
1AttrivisionAccuracy 89.4—Unverified