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

Showing 126–150 of 438 papers

TitleStatusHype
Efficient pedestrian detection by directly optimize the partial area under the ROC curve—0
Automatic Dataset Augmentation Using Virtual Human Simulation—0
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study—0
Nighttime Pedestrian Detection Based on Fore-Background Contrast Learning—0
Coupled Network for Robust Pedestrian Detection with Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling—0
Attention-Aware Multi-View Pedestrian Tracking—0
From Pedestrian Detection to Crosswalk Estimation: An EM Algorithm and Analysis on Diverse Datasets—0
Convolutional Neural Networks for Aerial Multi-Label Pedestrian Detection—0
A Method for Crash Prediction and Avoidance Using Hidden Markov Models—0
Fused Deep Neural Networks for Efficient Pedestrian Detection—0
Fused DNN: A deep neural network fusion approach to fast and robust pedestrian detection—0
A Survey of Vision Transformers in Autonomous Driving: Current Trends and Future Directions—0
Context-Sensitive Decision Forests for Object Detection—0
A lightweight YOLOv5-FFM model for occlusion pedestrian detection—0
Constraint-Aware Deep Neural Network Compression—0
Confidence-Rated Multiple Instance Boosting for Object Detection—0
A Study on Mitigating Hard Boundaries of Decision-Tree-based Uncertainty Estimates for AI Models—0
Adversarial Infrared Blocks: A Multi-view Black-box Attack to Thermal Infrared Detectors in Physical World—0
ASPED: An Audio Dataset for Detecting Pedestrians—0
Computer vision in automated parking systems: Design, implementation and challenges—0
A Shape Transformation-based Dataset Augmentation Framework for Pedestrian Detection—0
Comparing Computing Platforms for Deep Learning on a Humanoid Robot—0
A High-Performance HOG Extractor on FPGA—0
Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection—0
Comparing Apples and Oranges: Off-Road Pedestrian Detection on the NREC Agricultural Person-Detection Dataset—0
Show:102550
← PrevPage 6 of 18Next →

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