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
Data-Driven but Privacy-Conscious: Pedestrian Dataset De-identification via Full-Body Person Synthesis	Jun 20, 2023	De-identificationImage Generation	—Unverified
DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection	Mar 15, 2022	3D Object DetectionAutonomous Driving	—Unverified
Deep Learning based Pedestrian Detection at Distance in Smart Cities	Nov 18, 2018	DecoderDeep Learning	—Unverified
Deep Learning Strong Parts for Pedestrian Detection	Dec 1, 2015	Deep LearningOcclusion Handling	—Unverified
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation	Jun 15, 2022	Domain AdaptationInstance Segmentation	—Unverified
DeepSetNet: Predicting Sets with Deep Neural Networks	Nov 28, 2016	image-classificationImage Classification	—Unverified
Detector With Focus: Normalizing Gradient In Image Pyramid	Sep 5, 2019	object-detectionObject Detection	—Unverified
Diffusion Dataset Generation: Towards Closing the Sim2Real Gap for Pedestrian Detection	May 16, 2023	Dataset GenerationPedestrian Detection	—Unverified
DINF: Dynamic Instance Noise Filter for Occluded Pedestrian Detection	Jan 13, 2023	DenoisingPedestrian Detection	—Unverified
Discriminative Feature Transformation for Occluded Pedestrian Detection	Oct 1, 2019	Pedestrian Detection	—Unverified
Distance Estimation in Outdoor Driving Environments Using Phase-only Correlation Method with Event Cameras	May 23, 2025	Autonomous DrivingPedestrian Detection	—Unverified
Distant Pedestrian Detection in the Wild using Single Shot Detector with Deep Convolutional Generative Adversarial Networks	May 29, 2019	object-detectionObject Detection	—Unverified
DMRNet++: Learning Discriminative Features with Decoupled Networks and Enriched Pairs for One-Step Person Search	Nov 10, 2022	Pedestrian DetectionPerson Re-Identification	—Unverified
Dynamic Error-bounded Lossy Compression (EBLC) to Reduce the Bandwidth Requirement for Real-time Vision-based Pedestrian Safety Applications	Jan 29, 2020	Pedestrian DetectionVideo Compression	—Unverified
EdgeNet: Balancing Accuracy and Performance for Edge-based Convolutional Neural Network Object Detectors	Nov 14, 2019	object-detectionObject Detection	—Unverified
Efficient and Robust Pedestrian Detection using Deep Learning for Human-Aware Navigation	Jul 15, 2016	Human DetectionPedestrian Detection	—Unverified
Efficient Learning of Pinball TWSVM using Privileged Information and its applications	Jul 14, 2021	BIG-bench Machine LearningHandwritten Digit Recognition	—Unverified
Efficient pedestrian detection by directly optimize the partial area under the ROC curve	Oct 3, 2013	Ensemble Learningobject-detection	—Unverified
Efficient Pedestrian Detection in Top-View Fisheye Images Using Compositions of Perspective View Patches	Sep 6, 2020	Pedestrian Detection	—Unverified
Embracing Single Stride 3D Object Detector with Sparse Transformer	Dec 13, 2021	3D Object DetectionAutonomous Driving	—Unverified
End-to-End Detection and Re-identification Integrated Net for Person Search	Apr 2, 2018	Pedestrian DetectionPerson Search	—Unverified
End-to-end Person Search Sequentially Trained on Aggregated Dataset	Jan 24, 2022	Pedestrian DetectionPerson Search	—Unverified
Enhanced Cooperative Perception for Autonomous Vehicles Using Imperfect Communication	Apr 10, 2024	Autonomous Vehiclesobject-detection	—Unverified
Enhanced Multi-View Pedestrian Detection Using Probabilistic Occupancy Volume	Mar 14, 2025	3D Reconstructionmulti-view detection	—Unverified
Enhancing Multi-View Pedestrian Detection Through Generalized 3D Feature Pulling	Dec 20, 2023	multi-view detectionMultiview 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	YOLOv3 (Thermal)	mAP	82.7	—	Unverified
3	CFT	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