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 226–250 of 438 papers

Title	Date	Tasks	Status	Hype
Progressive Refinement Network for Occluded Pedestrian Detection	Aug 1, 2020	Body DetectionPedestrian Detection	—Unverified	0
Task-conditioned Domain Adaptation for Pedestrian Detection in Thermal Imagery	Aug 1, 2020	Domain AdaptationPedestrian Detection	CodeCode Available	1
Count- and Similarity-aware R-CNN for Pedestrian Detection	Aug 1, 2020	Human Instance SegmentationInstance Segmentation	CodeCode Available	0
Quantum-soft QUBO Suppression for Accurate Object Detection	Jul 28, 2020	Objectobject-detection	—Unverified	0
NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination	Jul 27, 2020	HallucinationObject Detection	CodeCode Available	1
YOLOpeds: Efficient Real-Time Single-Shot Pedestrian Detection for Smart Camera Applications	Jul 27, 2020	Autonomous DrivingDeep Learning	—Unverified	0
SADet: Learning An Efficient and Accurate Pedestrian Detector	Jul 26, 2020	Human DetectionPedestrian Detection	—Unverified	0
Multiview Detection with Feature Perspective Transformation	Jul 14, 2020	Human DetectionMultiview Detection	CodeCode Available	1
LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB	Jun 17, 2020	Autonomous VehiclesInstance Segmentation	—Unverified	0
Temporal-Context Enhanced Detection of Heavily Occluded Pedestrians	Jun 1, 2020	Pedestrian Detection	—Unverified	0
Resisting Crowd Occlusion and Hard Negatives for Pedestrian Detection in the Wild	May 15, 2020	object-detectionObject Detection	—Unverified	0
STINet: Spatio-Temporal-Interactive Network for Pedestrian Detection and Trajectory Prediction	May 8, 2020	3D geometryAutonomous Driving	—Unverified	0
Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module	Apr 18, 2020	Autonomous Drivingobject-detection	CodeCode Available	1
Gradient-based Feature Extraction From Raw Bayer Pattern Images	Apr 6, 2020	DemosaickingPedestrian Detection	—Unverified	0
The P-DESTRE: A Fully Annotated Dataset for Pedestrian Detection, Tracking, Re-Identification and Search from Aerial Devices	Apr 6, 2020	Pedestrian DetectionPerson Search	—Unverified	0
Near-chip Dynamic Vision Filtering for Low-Bandwidth Pedestrian Detection	Apr 3, 2020	Edge-computingPedestrian Detection	—Unverified	0
When Autonomous Systems Meet Accuracy and Transferability through AI: A Survey	Mar 29, 2020	DeblurringDecision Making	—Unverified	0
NMS by Representative Region: Towards Crowded Pedestrian Detection by Proposal Pairing	Mar 28, 2020	Pedestrian Detection	—Unverified	0
Pedestrian Detection with Wearable Cameras for the Blind: A Two-way Perspective	Mar 26, 2020	Pedestrian Detection	—Unverified	0
Detection in Crowded Scenes: One Proposal, Multiple Predictions	Mar 20, 2020	Object DetectionPedestrian Detection	CodeCode Available	2
Generalizable Pedestrian Detection: The Elephant In The Room	Mar 19, 2020	Autonomous DrivingPedestrian Detection	—Unverified	0
Adapted Center and Scale Prediction: More Stable and More Accurate	Feb 20, 2020	object-detectionObject Detection	CodeCode Available	1
An End-to-End Framework for Unsupervised Pose Estimation of Occluded Pedestrians	Feb 15, 2020	Domain AdaptationInstance Segmentation	—Unverified	0
Input Dropout for Spatially Aligned Modalities	Feb 7, 2020	Object TrackingPedestrian Detection	CodeCode Available	0
Measuring the Utilization of Public Open Spaces by Deep Learning: a Benchmark Study at the Detroit Riverfront	Feb 4, 2020	Activity RecognitionPedestrian 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