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
Illuminating Pedestrians via Simultaneous Detection & SegmentationCode0
Learning Scene-Pedestrian Graph for End to end Person SearchCode0
MVUDA: Unsupervised Domain Adaptation for Multi-view Pedestrian DetectionCode0
Efficient pedestrian detection by directly optimize the partial area under the ROC curve—0
Efficient Learning of Pinball TWSVM using Privileged Information and its applications—0
Box Re-Ranking: Unsupervised False Positive Suppression for Domain Adaptive Pedestrian Detection—0
Efficient and Robust Pedestrian Detection using Deep Learning for Human-Aware Navigation—0
Box-level Segmentation Supervised Deep Neural Networks for Accurate and Real-time Multispectral Pedestrian Detection—0
An Objective Method for Pedestrian Occlusion Level Classification—0
EdgeNet: Balancing Accuracy and Performance for Edge-based Convolutional Neural Network Object Detectors—0
Dynamic Error-bounded Lossy Compression (EBLC) to Reduce the Bandwidth Requirement for Real-time Vision-based Pedestrian Safety Applications—0
DMRNet++: Learning Discriminative Features with Decoupled Networks and Enriched Pairs for One-Step Person Search—0
Boosting-like Deep Learning For Pedestrian Detection—0
An FPGA-Accelerated Design for Deep Learning Pedestrian Detection in Self-Driving Vehicles—0
Adversarial Attacks on Event-Based Pedestrian Detectors: A Physical Approach—0
Distant Pedestrian Detection in the Wild using Single Shot Detector with Deep Convolutional Generative Adversarial Networks—0
Distance Estimation in Outdoor Driving Environments Using Phase-only Correlation Method with Event Cameras—0
Discriminative Feature Transformation for Occluded Pedestrian Detection—0
Booster-SHOT: Boosting Stacked Homography Transformations for Multiview Pedestrian Detection with Attention—0
DINF: Dynamic Instance Noise Filter for Occluded Pedestrian Detection—0
Diffusion Dataset Generation: Towards Closing the Sim2Real Gap for Pedestrian Detection—0
Detector With Focus: Normalizing Gradient In Image Pyramid—0
Birds Eye View Social Distancing Analysis System—0
An End-to-End Framework for Unsupervised Pose Estimation of Occluded Pedestrians—0
Adaptive NMS: Refining Pedestrian Detection in a Crowd—0
Show:102550
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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