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 1–50 of 438 papers

TitleStatusHype
YOLO-APD: Enhancing YOLOv8 for Robust Pedestrian Detection on Complex Road Geometries—0
Distance Estimation in Outdoor Driving Environments Using Phase-only Correlation Method with Event Cameras—0
Attention-Aware Multi-View Pedestrian Tracking—0
Panoramic Distortion-Aware Tokenization for Person Detection and Localization Using Transformers in Overhead Fisheye Images—0
Enhanced Multi-View Pedestrian Detection Using Probabilistic Occupancy Volume—0
Adversarial Attacks on Event-Based Pedestrian Detectors: A Physical Approach—0
PFSD: A Multi-Modal Pedestrian-Focus Scene Dataset for Rich Tasks in Semi-Structured EnvironmentsCode0
PedDet: Adaptive Spectral Optimization for Multimodal Pedestrian DetectionCode0
A Privacy Enhancing Technique to Evade Detection by Street Video Cameras Without Using Adversarial Accessories—0
Integrating LLMs with ITS: Recent Advances, Potentials, Challenges, and Future Directions—0
Multispectral Pedestrian Detection with Sparsely Annotated LabelCode1
Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic Dataset—0
Prediction of Occluded Pedestrians in Road Scenes using Human-like Reasoning: Insights from the OccluRoads Dataset—0
MVUDA: Unsupervised Domain Adaptation for Multi-view Pedestrian DetectionCode0
Revisiting Misalignment in Multispectral Pedestrian Detection: A Language-Driven Approach for Cross-modal Alignment Fusion—0
Hybrid Attention for Robust RGB-T Pedestrian Detection in Real-World Conditions—0
CAFF-DINO: Multi-spectral object detection transformers with cross-attention features fusion—0
GSON: A Group-based Social Navigation Framework with Large Multimodal Model—0
Real-Time Pedestrian Detection on IoT Edge Devices: A Lightweight Deep Learning Approach—0
MMDRFuse: Distilled Mini-Model with Dynamic Refresh for Multi-Modality Image FusionCode1
Mean Height Aided Post-Processing for Pedestrian Detection—0
Video-to-Text Pedestrian Monitoring (VTPM): Leveraging Computer Vision and Large Language Models for Privacy-Preserve Pedestrian Activity Monitoring at Intersections—0
A lightweight YOLOv5-FFM model for occlusion pedestrian detection—0
Toward Pedestrian Head Tracking: A Benchmark Dataset and an Information Fusion Network—0
Nighttime Pedestrian Detection Based on Fore-Background Contrast Learning—0
MambaST: A Plug-and-Play Cross-Spectral Spatial-Temporal Fuser for Efficient Pedestrian DetectionCode1
The Research of Group Re-identification from Multiple Cameras—0
Evaluating and Enhancing Trustworthiness of LLMs in Perception Tasks—0
When Pedestrian Detection Meets Multi-Modal Learning: Generalist Model and Benchmark DatasetCode2
GMC: A General Framework of Multi-stage Context Learning and Utilization for Visual Detection Tasks—0
Research, Applications and Prospects of Event-Based Pedestrian Detection: A Survey—0
Optimizing the image correction pipeline for pedestrian detection in the thermal-infrared domain—0
Pedestrian intention prediction in Adverse Weather Conditions with Spiking Neural Networks and Dynamic Vision Sensors—0
A PST Algorithm for FPs Suppression in Two-stage CNN Detection Methods—0
Predicting the Influence of Adverse Weather on Pedestrian Detection with Automotive Radar and Lidar Sensors—0
AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian DetectionCode1
Infrared Adversarial Car Stickers—0
MAML MOT: Multiple Object Tracking based on Meta-Learning—0
Imagine the Unseen: Occluded Pedestrian Detection via Adversarial Feature Completion—0
Robust Pedestrian Detection via Constructing Versatile Pedestrian Knowledge Bank—0
MiPa: Mixed Patch Infrared-Visible Modality Agnostic Object DetectionCode1
UniRGB-IR: A Unified Framework for RGB-Infrared Semantic Tasks via Adapter TuningCode2
FisheyeDetNet: 360° Surround view Fisheye Camera based Object Detection System for Autonomous Driving—0
Enhanced Cooperative Perception for Autonomous Vehicles Using Imperfect Communication—0
PathFinder: Attention-Driven Dynamic Non-Line-of-Sight Tracking with a Mobile Robot—0
MSCoTDet: Language-driven Multi-modal Fusion for Improved Multispectral Pedestrian Detection—0
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across EnvironmentsCode1
Data Augmentation in Human-Centric Vision—0
A Survey of Vision Transformers in Autonomous Driving: Current Trends and Future Directions—0
Causal Mode Multiplexer: A Novel Framework for Unbiased Multispectral Pedestrian DetectionCode1
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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
2YOLOv3 (Thermal) mAP82.7—Unverified
3CFT 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