SOTAVerified

Pedestrian Detection

Pedestrian detection is the task of detecting pedestrians from a camera.

Further state-of-the-art results (e.g. on the KITTI dataset) can be found at 3D Object Detection.

( Image credit: High-level Semantic Feature Detection: A New Perspective for Pedestrian Detection )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–100 of 438 papers

TitleStatusHype
A Flow-based Credibility Metric for Safety-critical Pedestrian Detection—0
INSANet: INtra-INter Spectral Attention Network for Effective Feature Fusion of Multispectral Pedestrian DetectionCode1
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving—0
Removal then Selection: A Coarse-to-Fine Fusion Perspective for RGB-Infrared Object DetectionCode2
Pedestrian Detection in Low-Light Conditions: A Comprehensive Survey—0
Generation of Synthetic Images for Pedestrian Detection Using a Sequence of GANs—0
Enhancing Multi-View Pedestrian Detection Through Generalized 3D Feature Pulling—0
Hulk: A Universal Knowledge Translator for Human-Centric TasksCode2
Optimizing Camera Configurations for Multi-View Pedestrian Detection—0
Paved2Paradise: Cost-Effective and Scalable LiDAR Simulation by Factoring the Real WorldCode1
Model-agnostic Body Part Relevance Assessment for Pedestrian Detection—0
Low-light Pedestrian Detection in Visible and Infrared Image Feeds: Issues and Challenges—0
Integrating Language-Derived Appearance Elements with Visual Cues in Pedestrian DetectionCode0
DDAM-PS: Diligent Domain Adaptive Mixer for Person SearchCode1
Visible to Thermal image Translation for improving visual task in low light conditions—0
Ranking-based Adaptive Query Generation for DETRs in Crowded Pedestrian Detection—0
Comparative study of multi-person tracking methods—0
HalluciDet: Hallucinating RGB Modality for Person Detection Through Privileged InformationCode1
Moiré Backdoor Attack (MBA): A Novel Trigger for Pedestrian Detectors in the Physical World—0
PPD: A New Valet Parking Pedestrian Fisheye Dataset for Autonomous Driving—0
PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement—0
Rethinking Cross-Domain Pedestrian Detection: A Background-Focused Distribution Alignment Framework for Instance-Free One-Stage DetectorsCode0
Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types—0
ASPED: An Audio Dataset for Detecting Pedestrians—0
An Energy-Aware Approach to Design Self-Adaptive AI-based Applications on the EdgeCode0
Cross-Modality Proposal-guided Feature Mining for Unregistered RGB-Thermal Pedestrian Detection—0
Stabilizing multispectral pedestrian detection with evidential hybrid fusion—0
VALERIE22 -- A photorealistic, richly metadata annotated dataset of urban environments—0
Learning Scene-Pedestrian Graph for End to end Person SearchCode0
Toward unlabeled multi-view 3D pedestrian detection by generalizable AI: techniques and performance analysis—0
Microvasculature Segmentation in Human BioMolecular Atlas Program (HuBMAP)—0
Bias Behind the Wheel: Fairness Testing of Autonomous Driving SystemsCode0
WCCNet: Wavelet-integrated CNN with Crossmodal Rearranging Fusion for Fast Multispectral Pedestrian Detection—0
ParGANDA: Making Synthetic Pedestrians A Reality For Object Detection—0
Nonlinear optical encoding enabled by recurrent linear scatteringCode1
Continual Learning for Out-of-Distribution Pedestrian DetectionCode0
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis—0
Multimodal Object Detection by Channel Switching and Spatial Attention—0
SDR-GAIN: A High Real-Time Occluded Pedestrian Pose Completion Method for Autonomous Driving—0
Pedestrian detection with high-resolution event camera—0
TFDet: Target-Aware Fusion for RGB-T Pedestrian DetectionCode1
Bright Channel Prior Attention for Multispectral Pedestrian Detection—0
Real-time Aerial Detection and Reasoning on Embedded-UAVs—0
Unsupervised Multi-view Pedestrian Detection—0
Selecting Learnable Training Samples is All DETRs Need in Crowded Pedestrian Detection—0
Diffusion Dataset Generation: Towards Closing the Sim2Real Gap for Pedestrian Detection—0
t-RAIN: Robust generalization under weather-aliasing label shift attacks—0
Self-Supervised Learning for Point Clouds Data: A Survey—0
Pedestrian Behavior Maps for Safety Advisories: CHAMP Framework and Real-World Data AnalysisCode0
6G Integrated Sensing and Communication: From Vision to Realization—0
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All datasetsCaltechCityPersonsLLVIPDVTODTJU-Ped-trafficTJU-Ped-campusCVC14Caltech Pedestrian DatasetMMPD-Dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UniHCP (FT)Heavy MR^-227.2—Unverified
2LDCFReasonable Miss Rate24.8—Unverified
3AlexNetReasonable Miss Rate23.3—Unverified
4TA-CNNReasonable Miss Rate20.9—Unverified
5Checkerboards+Reasonable Miss Rate17.1—Unverified
6NNNFReasonable Miss Rate16.2—Unverified
7Part-level CNN + saliency and bounding box alignmentReasonable Miss Rate12.4—Unverified
8CompACT-DeepReasonable Miss Rate11.75—Unverified
9MCFReasonable Miss Rate10.4—Unverified
10MS-CNNReasonable Miss Rate9.95—Unverified
#ModelMetricClaimedVerifiedStatus
1ACSP + EuroCity PersonsHeavy MR^-242.5—Unverified
2TLLReasonable MR^-215.5—Unverified
3FRCNNReasonable MR^-215.4—Unverified
4FRCNN+SegReasonable MR^-214.8—Unverified
5TLL+MRFReasonable MR^-214.4—Unverified
6RepLossReasonable MR^-213.2—Unverified
7OR-CNNReasonable MR^-212.8—Unverified
8ALFNetReasonable MR^-212—Unverified
9CSP (with offset) + ResNet-50Reasonable MR^-211—Unverified
10NOH-NMSReasonable MR^-210.8—Unverified
#ModelMetricClaimedVerifiedStatus
1INSANetlog average miss rate4.43—Unverified
2MMPedestronAP0.73—Unverified
3CAFF-DINOAP0.69—Unverified
4CFTAP0.64—Unverified
5UniRGB-IRAP0.63—Unverified
6RSDetAP0.61—Unverified
7CMXAP0.6—Unverified
8CSSAAP0.59—Unverified
9GAFFAP0.56—Unverified
10Halfway FusionAP0.55—Unverified
#ModelMetricClaimedVerifiedStatus
1YOLOv6 (Thermal) mAP84.4—Unverified
2CFT mAP82.7—Unverified
3YOLOv3 (Thermal) mAP82.7—Unverified
4CMX mAP81.6—Unverified
5YOLOv7 (Thermal)mAP77.8—Unverified
6YOLOv6 (Visible) mAP38.1—Unverified
7YOLOv7 (Visible)mAP35.3—Unverified
8YOLOv3 (Visible) mAP34.5—Unverified
#ModelMetricClaimedVerifiedStatus
1FCOSR (miss rate)24.35—Unverified
2RetinaNetR (miss rate)23.89—Unverified
3FPNR (miss rate)22.3—Unverified
4CrowdDetR (miss rate)20.82—Unverified
5EGCLR (miss rate)19.73—Unverified
6LSFMR (miss rate)18.7—Unverified
#ModelMetricClaimedVerifiedStatus
1RetinaNetR (miss rate)34.73—Unverified
2FCOSR (miss rate)31.89—Unverified
3CrowdDetR (miss rate)25.73—Unverified
4EGCLR (miss rate)24.84—Unverified
#ModelMetricClaimedVerifiedStatus
1CFTAP5078.2—Unverified
2CMXAP5068.9—Unverified
#ModelMetricClaimedVerifiedStatus
1LSFMMR0.87—Unverified
#ModelMetricClaimedVerifiedStatus
1MMPedestronbox mAP79—Unverified