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 151–200 of 438 papers

TitleStatusHype
A High-Performance HOG Extractor on FPGA—0
Joint Cascade Optimization Using A Product Of Boosted Classifiers—0
K-Tangent Spaces on Riemannian Manifolds for Improved Pedestrian Detection—0
Learning Lightweight Pedestrian Detector with Hierarchical Knowledge Distillation—0
Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection—0
Fused DNN: A deep neural network fusion approach to fast and robust pedestrian detection—0
Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection Dataset—0
Fused Deep Neural Networks for Efficient Pedestrian Detection—0
From Pedestrian Detection to Crosswalk Estimation: An EM Algorithm and Analysis on Diverse Datasets—0
Generalizable Multi-Camera 3D Pedestrian Detection—0
Comparative study of multi-person tracking methods—0
Generation of Synthetic Images for Pedestrian Detection Using a Sequence of GANs—0
GFD-SSD: Gated Fusion Double SSD for Multispectral Pedestrian Detection—0
Computer vision in automated parking systems: Design, implementation and challenges—0
Global-Local Dynamic Feature Alignment Network for Person Re-Identification—0
GMC: A General Framework of Multi-stage Context Learning and Utilization for Visual Detection Tasks—0
GPU-based Pedestrian Detection for Autonomous Driving—0
Gradient-based Camera Exposure Control for Outdoor Mobile Platforms—0
Gradient-based Feature Extraction From Raw Bayer Pattern Images—0
Graininess-Aware Deep Feature Learning for Pedestrian Detection—0
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving—0
GSON: A Group-based Social Navigation Framework with Large Multimodal Model—0
Adversarial Infrared Blocks: A Multi-view Black-box Attack to Thermal Infrared Detectors in Physical World—0
Combining LiDAR Space Clustering and Convolutional Neural Networks for Pedestrian Detection—0
Flexible Network Binarization with Layer-wise Priority—0
Hierarchical Adaptive Structural SVM for Domain Adaptation—0
A Robust Pedestrian Detection Approach for Autonomous Vehicles—0
How Far are We from Solving Pedestrian Detection?—0
Aggregated Channels Network for Real-Time Pedestrian Detection—0
FisheyeDetNet: 360° Surround view Fisheye Camera based Object Detection System for Autonomous Driving—0
Human Extraction and Scene Transition utilizing Mask R-CNN—0
Hybrid Attention for Robust RGB-T Pedestrian Detection in Real-World Conditions—0
Filtered Feature Channels for Pedestrian Detection—0
Hybrid Channel Based Pedestrian Detection—0
Filtered Channel Features for Pedestrian Detection—0
Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection—0
CircleNet: Reciprocating Feature Adaptation for Robust Pedestrian Detection—0
Imagine the Unseen: Occluded Pedestrian Detection via Adversarial Feature Completion—0
Impact of Power Supply Noise on Image Sensor Performance in Automotive Applications—0
Cross-Modality Proposal-guided Feature Mining for Unregistered RGB-Thermal Pedestrian Detection—0
A Real-Time Deep Learning Pedestrian Detector for Robot Navigation—0
Feature Calibration Network for Occluded Pedestrian Detection—0
BAANet: Learning Bi-directional Adaptive Attention Gates for Multispectral Pedestrian Detection—0
Increasing pedestrian detection performance through weighting of detection impairing factors—0
Characterisation of CMOS Image Sensor Performance in Low Light Automotive Applications—0
Informed Haar-like Features Improve Pedestrian Detection—0
Infrared Adversarial Car Stickers—0
Infrared image pedestrian target detection based on Yolov3 and migration learning—0
Fast Pedestrian Detection based on T-CENTRIST in infrared image—0
Fast Multiple-Part Based Object Detection Using KD-Ferns—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