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 151–175 of 438 papers

Title	Date	Tasks	Status
DeepSetNet: Predicting Sets with Deep Neural Networks	Nov 28, 2016	image-classificationImage Classification	—Unverified
Bi-box Regression for Pedestrian Detection and Occlusion Estimation	Sep 1, 2018	Occlusion EstimationPedestrian Detection	—Unverified
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation	Jun 15, 2022	Domain AdaptationInstance Segmentation	—Unverified
Beyond Domain Adaptation: Unseen Domain Encapsulation via Universal Non-volume Preserving Models	Dec 9, 2018	Domain AdaptationDomain Generalization	—Unverified
An Efficient Edge Detection Approach to Provide Better Edge Connectivity for Image Analysis	Mar 13, 2019	Edge DetectionFace Detection	—Unverified
Deep Learning Strong Parts for Pedestrian Detection	Dec 1, 2015	Deep LearningOcclusion Handling	—Unverified
Deep Learning based Pedestrian Detection at Distance in Smart Cities	Nov 18, 2018	DecoderDeep Learning	—Unverified
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection	Mar 15, 2022	3D Object DetectionAutonomous Driving	—Unverified
Beta R-CNN: Looking into Pedestrian Detection from Another Perspective	Oct 23, 2022	Pedestrian Detection	—Unverified
Adaptive Feature Fusion for Cooperative Perception using LiDAR Point Clouds	Jul 30, 2022	Domain Adaptationfeature selection	—Unverified
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis	Jun 20, 2023	De-identificationImage Generation	—Unverified
Benchmarking person re-identification approaches and training datasets for practical real-world implementations	Sep 29, 2021	BenchmarkingPedestrian Detection	—Unverified
Data Augmentation in Human-Centric Vision	Mar 13, 2024	Data AugmentationHuman Parsing	—Unverified
Basis Mapping Based Boosting for Object Detection	Jun 1, 2015	Objectobject-detection	—Unverified
BAANet: Learning Bi-directional Adaptive Attention Gates for Multispectral Pedestrian Detection	Dec 4, 2021	Pedestrian DetectionSpecificity	—Unverified
Adaptive Algorithm and Platform Selection for Visual Detection and Tracking	May 21, 2016	Pedestrian Detection	—Unverified
6G Integrated Sensing and Communication: From Vision to Realization	May 3, 2023	Integrated sensing and communicationISAC	—Unverified
Cross-Modality Proposal-guided Feature Mining for Unregistered RGB-Thermal Pedestrian Detection	Aug 23, 2023	Data AugmentationPedestrian Detection	—Unverified
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study	Aug 3, 2021	Autonomous DrivingHuman Detection	—Unverified
Automatic Dataset Augmentation Using Virtual Human Simulation	May 1, 2019	BIG-bench Machine LearningEvent Detection	—Unverified
Coupled Network for Robust Pedestrian Detection with Gated Multi-Layer Feature Extraction and Deformable Occlusion Handling	Dec 18, 2019	Occlusion HandlingPedestrian Detection	—Unverified
Convolutional Neural Networks for Aerial Multi-Label Pedestrian Detection	Jul 16, 2018	Action DetectionObject	—Unverified
Attention-Aware Multi-View Pedestrian Tracking	Apr 3, 2025	Multi-Object TrackingObject Tracking	—Unverified
A Method for Crash Prediction and Avoidance Using Hidden Markov Models	Dec 22, 2022	Pedestrian Detection	—Unverified
GSON: A Group-based Social Navigation Framework with Large Multimodal Model	Sep 26, 2024	Autonomous VehiclesMotion Planning	—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