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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 376–400 of 438 papers

Title	Date	Tasks	Status	Hype
Real-Time RGB-D based Template Matching Pedestrian Detection	Oct 3, 2016	Pedestrian DetectionTemplate Matching	—Unverified	0
Linear Support Tensor Machine: Pedestrian Detection in Thermal Infrared Images	Sep 26, 2016	AttributePedestrian Detection	CodeCode Available	0
Reduced Memory Region Based Deep Convolutional Neural Network Detection	Sep 8, 2016	Pedestrian Detection	—Unverified	0
A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection	Jul 25, 2016	Face DetectionFeature Upsampling	CodeCode Available	0
Is Faster R-CNN Doing Well for Pedestrian Detection?	Jul 24, 2016	Objectobject-detection	—Unverified	0
A Real-Time Deep Learning Pedestrian Detector for Robot Navigation	Jul 15, 2016	Deep LearningPedestrian Detection	—Unverified	0
Efficient and Robust Pedestrian Detection using Deep Learning for Human-Aware Navigation	Jul 15, 2016	Human DetectionPedestrian Detection	—Unverified	0
LCrowdV: Generating Labeled Videos for Simulation-based Crowd Behavior Learning	Jun 29, 2016	General ClassificationPedestrian Detection	—Unverified	0
Semantic Channels for Fast Pedestrian Detection	Jun 1, 2016	CPUGPU	—Unverified	0
Large Scale Hard Sample Mining With Monte Carlo Tree Search	Jun 1, 2016	Face Detectionobject-detection	—Unverified	0
Adaptive Algorithm and Platform Selection for Visual Detection and Tracking	May 21, 2016	Pedestrian Detection	—Unverified	0
Person Re-identification in the Wild	Apr 9, 2016	BenchmarkingPedestrian Detection	—Unverified	0
Joint Detection and Identification Feature Learning for Person Search	Apr 7, 2016	Pedestrian DetectionPerson Re-Identification	CodeCode Available	0
Pushing the Limits of Deep CNNs for Pedestrian Detection	Mar 15, 2016	Occlusion HandlingOptical Flow Estimation	—Unverified	0
Learning Multilayer Channel Features for Pedestrian Detection	Mar 1, 2016	Pedestrian Detection	—Unverified	0
How Far are We from Solving Pedestrian Detection?	Feb 3, 2016	ClusteringPedestrian Detection	—Unverified	0
Deep Learning Strong Parts for Pedestrian Detection	Dec 1, 2015	Deep LearningOcclusion Handling	—Unverified	0
Object Detection Using Generalization and Efficiency Balanced Co-Occurrence Features	Dec 1, 2015	feature selectionObject	—Unverified	0
Pedestrian Detection Inspired by Appearance Constancy and Shape Symmetry	Nov 25, 2015	Pedestrian Detection	—Unverified	0
A convnet for non-maximum suppression	Nov 19, 2015	ClusteringObject	—Unverified	0
Scale-aware Fast R-CNN for Pedestrian Detection	Oct 28, 2015	Pedestrian DetectionPhilosophy	—Unverified	0
Deep convolutional neural networks for pedestrian detection	Oct 13, 2015	image-classificationImage Classification	CodeCode Available	0
Fast Algorithms for Convolutional Neural Networks	Sep 30, 2015	GPUPedestrian Detection	CodeCode Available	2
Learning Complexity-Aware Cascades for Deep Pedestrian Detection	Jul 19, 2015	Pedestrian Detection	—Unverified	0
Filtered Feature Channels for Pedestrian Detection	Jun 1, 2015	Optical Flow EstimationPedestrian Detection	—Unverified	0

Show:10 25 50

← PrevPage 16 of 18Next →

All datasets Caltech CityPersons LLVIP DVTOD TJU-Ped-traffic TJU-Ped-campus CVC14 Caltech Pedestrian Dataset MMPD-Dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	UniHCP (FT)	Heavy MR^-2	27.2	—	Unverified
2	LDCF	Reasonable Miss Rate	24.8	—	Unverified
3	AlexNet	Reasonable Miss Rate	23.3	—	Unverified
4	TA-CNN	Reasonable Miss Rate	20.9	—	Unverified
5	Checkerboards+	Reasonable Miss Rate	17.1	—	Unverified
6	NNNF	Reasonable Miss Rate	16.2	—	Unverified
7	Part-level CNN + saliency and bounding box alignment	Reasonable Miss Rate	12.4	—	Unverified
8	CompACT-Deep	Reasonable Miss Rate	11.75	—	Unverified
9	MCF	Reasonable Miss Rate	10.4	—	Unverified
10	MS-CNN	Reasonable Miss Rate	9.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACSP + EuroCity Persons	Heavy MR^-2	42.5	—	Unverified
2	TLL	Reasonable MR^-2	15.5	—	Unverified
3	FRCNN	Reasonable MR^-2	15.4	—	Unverified
4	FRCNN+Seg	Reasonable MR^-2	14.8	—	Unverified
5	TLL+MRF	Reasonable MR^-2	14.4	—	Unverified
6	RepLoss	Reasonable MR^-2	13.2	—	Unverified
7	OR-CNN	Reasonable MR^-2	12.8	—	Unverified
8	ALFNet	Reasonable MR^-2	12	—	Unverified
9	CSP (with offset) + ResNet-50	Reasonable MR^-2	11	—	Unverified
10	NOH-NMS	Reasonable MR^-2	10.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	INSANet	log average miss rate	4.43	—	Unverified
2	MMPedestron	AP	0.73	—	Unverified
3	CAFF-DINO	AP	0.69	—	Unverified
4	CFT	AP	0.64	—	Unverified
5	UniRGB-IR	AP	0.63	—	Unverified
6	RSDet	AP	0.61	—	Unverified
7	CMX	AP	0.6	—	Unverified
8	CSSA	AP	0.59	—	Unverified
9	GAFF	AP	0.56	—	Unverified
10	Halfway Fusion	AP	0.55	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	YOLOv6 (Thermal)	mAP	84.4	—	Unverified
2	CFT	mAP	82.7	—	Unverified
3	YOLOv3 (Thermal)	mAP	82.7	—	Unverified
4	CMX	mAP	81.6	—	Unverified
5	YOLOv7 (Thermal)	mAP	77.8	—	Unverified
6	YOLOv6 (Visible)	mAP	38.1	—	Unverified
7	YOLOv7 (Visible)	mAP	35.3	—	Unverified
8	YOLOv3 (Visible)	mAP	34.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FCOS	R (miss rate)	24.35	—	Unverified
2	RetinaNet	R (miss rate)	23.89	—	Unverified
3	FPN	R (miss rate)	22.3	—	Unverified
4	CrowdDet	R (miss rate)	20.82	—	Unverified
5	EGCL	R (miss rate)	19.73	—	Unverified
6	LSFM	R (miss rate)	18.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RetinaNet	R (miss rate)	34.73	—	Unverified
2	FCOS	R (miss rate)	31.89	—	Unverified
3	CrowdDet	R (miss rate)	25.73	—	Unverified
4	EGCL	R (miss rate)	24.84	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CFT	AP50	78.2	—	Unverified
2	CMX	AP50	68.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LSFM	MR	0.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MMPedestron	box mAP	79	—	Unverified