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 201–250 of 438 papers

TitleStatusHype
Pedestrian Detection by Exemplar-Guided Contrastive Learning—0
Benchmarking person re-identification approaches and training datasets for practical real-world implementations—0
Traffic-Net: 3D Traffic Monitoring Using a Single Camera—0
Global-Local Dynamic Feature Alignment Network for Person Re-Identification—0
A Pedestrian Detection and Tracking Framework for Autonomous Cars: Efficient Fusion of Camera and LiDAR Data—0
Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains—0
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study—0
Multi-Modal Pedestrian Detection with Large Misalignment Based on Modal-Wise Regression and Multi-Modal IoU—0
You Better Look Twice: a new perspective for designing accurate detectors with reduced computations—0
Efficient Learning of Pinball TWSVM using Privileged Information and its applications—0
To the Point: Efficient 3D Object Detection in the Range Image with Graph Convolution Kernels—0
Spatio-Contextual Deep Network Based Multimodal Pedestrian Detection For Autonomous Driving—0
Improved Instance Discrimination and Feature Compactness for End-to-End Person SearchCode0
Large-Scale Unsupervised Person Re-Identification with Contrastive Learning—0
Verification of Size Invariance in DNN Activations using Concept Embeddings—0
Stable and Effective One-Step Method for Person Search—0
Pedestrian Detection in 3D Point Clouds using Deep Neural Networks—0
Segmentation-Based Bounding Box Generation for Omnidirectional Pedestrian Detection—0
Computer vision in automated parking systems: Design, implementation and challenges—0
Variational Pedestrian Detection—0
Generalizable Multi-Camera 3D Pedestrian Detection—0
V2F-Net: Explicit Decomposition of Occluded Pedestrian Detection—0
Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection—0
Multi-Scale Feature Pyramid Network: A Heavily Occluded Pedestrian Detection Network Based on ResNet—0
Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person SearchCode0
Robust pedestrian detection in thermal imagery using synthesized images—0
Box Re-Ranking: Unsupervised False Positive Suppression for Domain Adaptive Pedestrian Detection—0
Single Shot Multitask Pedestrian Detection and Behavior Prediction—0
Stacked Homography Transformations for Multi-View Pedestrian Detection—0
Robust Small-Scale Pedestrian Detection With Cued Recall via Memory Learning—0
Infrared image pedestrian target detection based on Yolov3 and migration learning—0
Where, What, Whether: Multi-modal Learning Meets Pedestrian Detection—0
Robust Real-Time Pedestrian Detection on Embedded Devices—0
Characterisation of CMOS Image Sensor Performance in Low Light Automotive Applications—0
Impact of Power Supply Noise on Image Sensor Performance in Automotive Applications—0
Mutual-Supervised Feature Modulation Network for Occluded Pedestrian Detection—0
Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learningCode0
SemanticVoxels: Sequential Fusion for 3D Pedestrian Detection using LiDAR Point Cloud and Semantic Segmentation—0
Efficient Pedestrian Detection in Top-View Fisheye Images Using Compositions of Perspective View Patches—0
Visible Feature Guidance for Crowd Pedestrian Detection—0
Progressive Refinement Network for Occluded Pedestrian Detection—0
Count- and Similarity-aware R-CNN for Pedestrian DetectionCode0
Quantum-soft QUBO Suppression for Accurate Object Detection—0
YOLOpeds: Efficient Real-Time Single-Shot Pedestrian Detection for Smart Camera Applications—0
SADet: Learning An Efficient and Accurate Pedestrian Detector—0
LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB—0
Temporal-Context Enhanced Detection of Heavily Occluded Pedestrians—0
Resisting Crowd Occlusion and Hard Negatives for Pedestrian Detection in the Wild—0
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction—0
Gradient-based Feature Extraction From Raw Bayer Pattern Images—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