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 276–300 of 438 papers

TitleStatusHype
WILDTRACK: A Multi-Camera HD Dataset for Dense Unscripted Pedestrian Detection—0
Word Channel Based Multiscale Pedestrian Detection Without Image Resizing and Using Only One Classifier—0
YOLO-APD: Enhancing YOLOv8 for Robust Pedestrian Detection on Complex Road Geometries—0
YOLOpeds: Efficient Real-Time Single-Shot Pedestrian Detection for Smart Camera Applications—0
Local Decorrelation For Improved Pedestrian Detection—0
Localized Semantic Feature Mixers for Efficient Pedestrian Detection in Autonomous Driving—0
Low-light Pedestrian Detection in Visible and Infrared Image Feeds: Issues and Challenges—0
LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB—0
MAML MOT: Multiple Object Tracking based on Meta-Learning—0
Mean Height Aided Post-Processing for Pedestrian Detection—0
Measuring the Utilization of Public Open Spaces by Deep Learning: a Benchmark Study at the Detroit Riverfront—0
Mesh-SORT: Simple and effective location-wise tracker with lost management strategies—0
Microvasculature Segmentation in Human BioMolecular Atlas Program (HuBMAP)—0
MixedPeds: Pedestrian Detection in Unannotated Videos using Synthetically Generated Human-agents for Training—0
Model-agnostic Body Part Relevance Assessment for Pedestrian Detection—0
Modeling Mutual Visibility Relationship in Pedestrian Detection—0
Moiré Backdoor Attack (MBA): A Novel Trigger for Pedestrian Detectors in the Physical World—0
MSCoTDet: Language-driven Multi-modal Fusion for Improved Multispectral Pedestrian Detection—0
Multi-Label Learning of Part Detectors for Heavily Occluded Pedestrian Detection—0
Multimodal Object Detection by Channel Switching and Spatial Attention—0
Multi-Modal Pedestrian Detection with Large Misalignment Based on Modal-Wise Regression and Multi-Modal IoU—0
Multi-Scale Feature Pyramid Network: A Heavily Occluded Pedestrian Detection Network Based on ResNet—0
Multispectral Pedestrian Detection: Benchmark Dataset and Baseline—0
Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset—0
Mutual-Supervised Feature Modulation Network for Occluded Pedestrian Detection—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