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 326–350 of 438 papers

Title	Date	Tasks	Status	Hype
Object Detection with Deep Learning: A Review	Jul 15, 2018	Deep LearningFace Detection	—Unverified	0
Robustness Analysis of Pedestrian Detectors for Surveillance	Jul 12, 2018	Pedestrian Detection	CodeCode Available	0
Small-scale Pedestrian Detection Based on Somatic Topology Localization and Temporal Feature Aggregation	Jul 4, 2018	Pedestrian Detection	—Unverified	0
A Content-Based Late Fusion Approach Applied to Pedestrian Detection	Jun 8, 2018	Pedestrian Detection	—Unverified	0
WILDTRACK: A Multi-Camera HD Dataset for Dense Unscripted Pedestrian Detection	Jun 1, 2018	multi-view detectionMultiview Detection	—Unverified	0
Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors	Jun 1, 2018	Occlusion HandlingPedestrian Detection	—Unverified	0
Exploit the Unknown Gradually: One-Shot Video-Based Person Re-Identification by Stepwise Learning	Jun 1, 2018	One-Shot LearningPedestrian Detection	—Unverified	0
Occluded Pedestrian Detection Through Guided Attention in CNNs	Jun 1, 2018	Pedestrian Detection	—Unverified	0
Disparity Sliding Window: Object Proposals From Disparity Images	May 17, 2018	Objectobject-detection	CodeCode Available	0
Fused Deep Neural Networks for Efficient Pedestrian Detection	May 2, 2018	Ensemble LearningGeneral Classification	—Unverified	0
CrowdHuman: A Benchmark for Detecting Human in a Crowd	Apr 30, 2018	DiversityHuman Detection	CodeCode Available	1
PCN: Part and Context Information for Pedestrian Detection with CNNs	Apr 12, 2018	Occlusion HandlingPedestrian Detection	—Unverified	0
YOLOv3: An Incremental Improvement	Apr 8, 2018	ClassificationObject Detection	CodeCode Available	1
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond	Apr 5, 2018	Generative Adversarial NetworkPedestrian Detection	CodeCode Available	0
Exploring Multi-Branch and High-Level Semantic Networks for Improving Pedestrian Detection	Apr 3, 2018	object-detectionObject Detection	—Unverified	0
End-to-End Detection and Re-identification Integrated Net for Person Search	Apr 2, 2018	Pedestrian DetectionPerson Search	—Unverified	0
Illumination-aware Faster R-CNN for Robust Multispectral Pedestrian Detection	Mar 14, 2018	Multispectral Object DetectionPedestrian Detection	—Unverified	0
Fusion of Multispectral Data Through Illumination-aware Deep Neural Networks for Pedestrian Detection	Feb 27, 2018	Autonomous DrivingMultispectral Object Detection	—Unverified	0
Unsupervised Deep Domain Adaptation for Pedestrian Detection	Feb 9, 2018	Domain AdaptationPedestrian Detection	—Unverified	0
A High-Performance HOG Extractor on FPGA	Jan 12, 2018	Pedestrian DetectionVocal Bursts Intensity Prediction	—Unverified	0
Aggregated Channels Network for Real-Time Pedestrian Detection	Jan 1, 2018	GPUPedestrian Detection	—Unverified	0
Scene-Specific Pedestrian Detection Based on Parallel Vision	Dec 23, 2017	object-detectionObject Detection	CodeCode Available	0
Repulsion Loss: Detecting Pedestrians in a Crowd	Nov 21, 2017	Pedestrian Detectionregression	CodeCode Available	0
Combining LiDAR Space Clustering and Convolutional Neural Networks for Pedestrian Detection	Oct 17, 2017	Autonomous VehiclesClustering	—Unverified	0
Multi-Label Learning of Part Detectors for Heavily Occluded Pedestrian Detection	Oct 1, 2017	Multi-Label LearningPedestrian Detection	—Unverified	0

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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