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 276–300 of 438 papers

Title	Date	Tasks	Status
The Pedestrian Patterns Dataset	Jan 6, 2020	Autonomous DrivingAutonomous Vehicles	—Unverified
The Research of Group Re-identification from Multiple Cameras	Jul 19, 2024	Graph MatchingPedestrian Detection	—Unverified
The WILDTRACK Multi-Camera Person Dataset	Jul 28, 2017	Camera CalibrationPedestrian Detection	—Unverified
To Boost or Not to Boost? On the Limits of Boosted Trees for Object Detection	Jan 6, 2017	Face Detectionobject-detection	—Unverified
Too Far to See? Not Really! --- Pedestrian Detection with Scale-aware Localization Policy	Sep 1, 2017	Pedestrian DetectionRegion Proposal	—Unverified
To the Point: Efficient 3D Object Detection in the Range Image with Graph Convolution Kernels	Jun 25, 2021	3D Object DetectionGraph Neural Network	—Unverified
Toward Pedestrian Head Tracking: A Benchmark Dataset and an Information Fusion Network	Aug 12, 2024	Autonomous DrivingCollision Avoidance	—Unverified
Toward unlabeled multi-view 3D pedestrian detection by generalizable AI: techniques and performance analysis	Aug 8, 2023	Pedestrian Detection	—Unverified
Traffic-Net: 3D Traffic Monitoring Using a Single Camera	Sep 19, 2021	3D Object DetectionCamera Auto-Calibration	—Unverified
t-RAIN: Robust generalization under weather-aliasing label shift attacks	May 15, 2023	Autonomous VehiclesData Augmentation	—Unverified
Translation, Scale and Rotation: Cross-Modal Alignment Meets RGB-Infrared Vehicle Detection	Sep 28, 2022	2D Object Detectioncross-modal alignment	—Unverified
Understanding the Impact of Edge Cases from Occluded Pedestrians for ML Systems	Apr 26, 2022	Body Detectionobject-detection	—Unverified
Unsupervised Deep Domain Adaptation for Pedestrian Detection	Feb 9, 2018	Domain AdaptationPedestrian Detection	—Unverified
Unsupervised Domain Adaptation for Multispectral Pedestrian Detection	Apr 7, 2019	Autonomous DrivingDomain Adaptation	—Unverified
Unsupervised Hard Example Mining from Videos for Improved Object Detection	Aug 13, 2018	Face Detectionobject-detection	—Unverified
Unsupervised Multi-view Pedestrian Detection	May 21, 2023	Camera CalibrationPedestrian Detection	—Unverified
V2F-Net: Explicit Decomposition of Occluded Pedestrian Detection	Apr 7, 2021	Object DetectionPedestrian Detection	—Unverified
VALERIE22 -- A photorealistic, richly metadata annotated dataset of urban environments	Aug 18, 2023	Pedestrian Detection	—Unverified
Variational Pedestrian Detection	Apr 26, 2021	object-detectionObject Detection	—Unverified
Verification of Size Invariance in DNN Activations using Concept Embeddings	May 14, 2021	Pedestrian Detection	—Unverified
Video-to-Text Pedestrian Monitoring (VTPM): Leveraging Computer Vision and Large Language Models for Privacy-Preserve Pedestrian Activity Monitoring at Intersections	Aug 21, 2024	4kPedestrian Detection	—Unverified
Virtual to Real adaptation of Pedestrian Detectors	Jan 9, 2020	Domain Adaptationobject-detection	—Unverified
Visible Feature Guidance for Crowd Pedestrian Detection	Aug 23, 2020	Pedestrian Detection	—Unverified
Visible to Thermal image Translation for improving visual task in low light conditions	Oct 31, 2023	Image-to-Image TranslationPedestrian Detection	—Unverified
WCCNet: Wavelet-integrated CNN with Crossmodal Rearranging Fusion for Fast Multispectral Pedestrian Detection	Aug 2, 2023	Computational EfficiencyPedestrian Detection	—Unverified

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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