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 301–350 of 438 papers

TitleStatusHype
What Can Help Pedestrian Detection?—0
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey—0
Where, What, Whether: Multi-modal Learning Meets Pedestrian Detection—0
Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection—0
WIDER Face and Pedestrian Challenge 2018: Methods and Results—0
WiderPerson: A Diverse Dataset for Dense Pedestrian Detection in the Wild—0
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
You Better Look Twice: a new perspective for designing accurate detectors with reduced computations—0
Evaluating and Enhancing Trustworthiness of LLMs in Perception Tasks—0
Nighttime Pedestrian Detection Based on Fore-Background Contrast Learning—0
6G Integrated Sensing and Communication: From Vision to Realization—0
A Content-Based Late Fusion Approach Applied to Pedestrian Detection—0
A convnet for non-maximum suppression—0
Adaptive Algorithm and Platform Selection for Visual Detection and Tracking—0
Adaptive Feature Fusion for Cooperative Perception using LiDAR Point Clouds—0
Adaptive NMS: Refining Pedestrian Detection in a Crowd—0
Adversarial Attacks on Event-Based Pedestrian Detectors: A Physical Approach—0
A-Eye: Driving with the Eyes of AI for Corner Case Generation—0
A Flow-based Credibility Metric for Safety-critical Pedestrian Detection—0
Age and gender bias in pedestrian detection algorithms—0
Aggregated Channels Network for Real-Time Pedestrian Detection—0
A High-Performance HOG Extractor on FPGA—0
A lightweight YOLOv5-FFM model for occlusion pedestrian detection—0
A Method for Crash Prediction and Avoidance Using Hidden Markov Models—0
An Efficient Edge Detection Approach to Provide Better Edge Connectivity for Image Analysis—0
An End-to-End Framework for Unsupervised Pose Estimation of Occluded Pedestrians—0
An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles—0
An Objective Method for Pedestrian Occlusion Level Classification—0
A Pedestrian Detection and Tracking Framework for Autonomous Cars: Efficient Fusion of Camera and LiDAR Data—0
Application of image-to-image translation in improving pedestrian detection—0
A Privacy Enhancing Technique to Evade Detection by Street Video Cameras Without Using Adversarial Accessories—0
A PST Algorithm for FPs Suppression in Two-stage CNN Detection Methods—0
A Real-Time Deep Learning Pedestrian Detector for Robot Navigation—0
A Robust Pedestrian Detection Approach for Autonomous Vehicles—0
A Safety-Adapted Loss for Pedestrian Detection in Automated Driving—0
A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection—0
ASPED: An Audio Dataset for Detecting Pedestrians—0
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models—0
A Survey of Vision Transformers in Autonomous Driving: Current Trends and Future Directions—0
Attention-Aware Multi-View Pedestrian Tracking—0
Automatic Dataset Augmentation Using Virtual Human Simulation—0
BAANet: Learning Bi-directional Adaptive Attention Gates for Multispectral Pedestrian Detection—0
Basis Mapping Based Boosting for Object Detection—0
Benchmarking person re-identification approaches and training datasets for practical real-world implementations—0
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective—0
Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models—0
Bi-box Regression for Pedestrian Detection and Occlusion Estimation—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