This project provides a paper list about pedestrian detection following the taxonomy in "From Handcrafted to Deep Features for Pedestrian Detection: A Survey (IEEE TPAMI 2022)".
**PD**: Pedestrian Detection; **MPD**: Multispectral Pedestrian Detection; **MVD**: Multi-View Pedestrian Detection; **Others**: Pedestrian Detection with Special Devices
Scale-aware methods
Exploit all the layers: Fast and accurate cnn object detector with scale dependent pooling and cascaded rejection classifiers, CVPR 2016. [Paper]
A unified multi-scale deep convolutional neural network for fast object detection, ECCV 2016. [Paper]
Scale-adaptive deconvolutional regression network for pedestrian detection, ACCV 2016. [Paper]
Sam-rcnn: Scaleaware multi-resolution multi-channel pedestrian detection, BMVC 2018. [Paper]
Fpn++: A simple baseline for pedestrian detection, ICME 2019. [Paper]
Ratio-and-scale-aware YOLO for pedestrian detection, TIP 2019. [Paper]
Part-based methods
PCN: Part and context information for pedestrian detection with cnns, BMVC 2017. [Paper]
Joint holistic and partial cnn for pedestrian detection, BMVC 2018. [Paper]
Occlusion-aware r-cnn: Detecting pedestrians in a crowd, ECCV 2018. [Paper]
Bi-box regression for pedestrian detection and occlusion estimation, ECCV 2018. [Paper]
Pedjointnet: Joint headshoulder and full body deep network for pedestrian detection, IEEE Access 2019. [Paper]
Double anchor r-cnn for human detection in a crowd, arXiv 2019. [Paper]
Semantic head enhanced pedestrian detection in a crowd, arXiv 2019. [Paper]
Semantic part rcnn for real-world pedestrian detection, CVPRW 2019. [Paper]
Mask-guided attention network for occluded pedestrian detection, ICCV 2019. [Paper]
Learning Hierarchical Graph for Occluded Pedestrian Detection, ACM-MM 2020. [Paper]
A Part-Aware Multi-Scale Fully Convolutional Network for Pedestrian Detection, TITS 2021. [Paper]
Sequential Attention-Based Distinct Part Modeling for Balanced Pedestrian Detection, TITS 2022. [Paper]
Attention-based methods
Illuminating pedestrians via simultaneous detection and segmentation, ICCV 2017. [Paper]
Vis-hud: Using visual saliency to improve human detection with convolutional neural networks, CVPRW 2018. [Paper]
Graininess-aware deep feature learning for pedestrian detection, ECCV 2018. [Paper]
Occluded pedestrian detection through guided attention in cnns, CVPR 2018. [Paper]
Deep feature fusion by competitive attention for pedestrian detection, IEEE Access 2019. [Paper]
Part-level convolutional neural networks for pedestrian detection using saliency and boundary box alignment, IEEE Access 2019. [Paper]
Multi-grained deep feature learning for robust pedestrian detection, TCSVT 2019. [Paper]
Attention guided neural network models for occluded pedestrian detection, PR 2020. [Paper]
Feature-fused methods
Direct multi-scale dual-stream network for pedestrian detection, ICIP 2017. [Paper]
Accurate single stage detector using recurrent rolling convolution, CVPR 2017. [Paper]
Object detection based on multilayer convolution feature fusion and online hard example mining, IEEE Access 2018. [Paper]
Pedestrian detection via body part semantic and contextual information with dnn, TMM 2018. [Paper]
Deep aggregation learning for high-performance small pedestrian detection, ACML 2018. [Paper]
Learning pixel-level and instance-level context-aware features for pedestrian detection in crowds, IEEE Access 2019. [Paper]
Mfr-cnn: Incorporating multi-scale features and global information for traffic object detection, TVT 2019. [Paper]
Taking a look at small-scale pedestrians and occluded pedestrians, TIP 2020. [Paper]
Coupled network for robust pedestrian detection with gated multi-layer feature extraction and deformable occlusion handling, TIP2021. [Paper]
Object detection with location-aware deformable convolution and backward attention filtering, CVPR 2019. [Paper]
Temporal-context enhanced detection of heavily occluded pedestrians, CVPR 2020. [Paper]
Ground plane context aggregation network for day-and-night on vehicular pedestrian detection, TITS 2020. [Paper]
Vehicle and Pedestrian Detection Algorithm Based on Lightweight YOLOv3-Promote and Semi-Precision Acceleration, TITS 2022. [Paper]
High quality proposal feature generation for crowded pedestrian detection, PR 2022. [Paper]
Multimodal pedestrian detection using metaheuristics with deep convolutional neural network in crowded scenes, IF 2022. [Paper]
Localized Semantic Feature Mixers for Efficient Pedestrian Detection in Autonomous Driving, CVPR 2023. [Paper]
Cascade-based methods
Fused dnn: A deep neural network fusion approach to fast and robust pedestrian detection, WACV 2017. [Paper]
Learning efficient single-stage pedestrian detectors by asymptotic localization fitting, ECCV 2018. [Paper]
Circlenet: Reciprocating feature adaptation for robust pedestrian detection, TITS 2019. [Paper]
Pedestrian detection with autoregressive network phases, CVPR 2019. [Paper]
Pedestrian detection: The elephant in the room, arXiv 2020. [Paper]
A one-and-half stage pedestrian detector, WACV 2020. [Paper]
Progressive Refinement Network for Occluded Pedestrian Detection, ECCV 2020. [Paper]
SADet: Learning An Efficient and Accurate Pedestrian Detector, IJCB 2021. [Paper]
F2DNet: Fast Focal Detection Network for Pedestrian Detection, ICPR 2022. [Paper]
Anchor-free methods
Small-scale pedestrian detection based on topological line localization and temporal feature aggregation, ECCV 2018. [Paper]
High-level semantic feature detection: A new perspective for pedestrian detection, CVPR 2019. [Paper]
Attribute-aware pedestrian detection in a crowd, TMM 2021. [Paper]
OAF-Net: An Occlusion-Aware Anchor-Free Network for Pedestrian Detection in a Crowd, TITS 2022. [Paper]
Effectiveness of Vision Transformer for Fast and Accurate Single-Stage Pedestrian Detection, NeurIPS 2022. [Paper]
Cascade Transformer Decoder based Occluded Pedestrian Detection with Dynamic Deformable Convolution and Gaussian Projection Channel Attention Mechanism, TMM 2023. [Paper]
Pedestrian Detection Using MB-CSP Model and Boosted Identity Aware Non-Maximum Suppression, TITS 2022. [Paper]
Optimal Proposal Learning for Deployable End-to-End Pedestrian Detection, CVPR 2023. [Paper]
CFRLA-Net: A Context-aware Feature Representation Learning Anchor-free Network for Pedestrian Detection, TCSVT2023. [Paper]
Data-augmentation methods
Synthesizing a scene-specific pedestrian detector and pose estimator for static video surveillance, IJCV 2018. [Paper]
Training cascade compact cnn with region-iou for accurate pedestrian detection, TITS 2019. [Paper]
A shape transformation-based dataset augmentation framework for pedestrian detection, arXiv 2019. [Paper]
Advanced pedestrian dataset augmentation for autonomous driving, ICCVW 2019. [Paper]
Pmc-gans: Generating multi-scale high-quality pedestrian with multimodal cascaded gans, BMVC 2019. [Paper]
Pedhunter: Occlusion robust pedestrian detector in crowded scenes, AAAI 2020. [Paper]
Where, what, whether: Multi-modal learning meets pedestrian detection, CVPR 2020. [Paper]
Low-illumination image enhancement for night-time uav pedestrian detection, TII 2020. [Paper]
AutoPedestrian: An Automatic Data Augmentation and Loss Function Search Scheme for Pedestrian Detection, TIP 20201. [Paper]
Impartial Differentiable Automatic Data Augmentation Based on Finite Difference Approximation for Pedestrian Detection, TIM 2022. [Paper]
Pedestrian Detection Using Multi-Scale Structure-Enhanced Super-Resolution, IEEE TITS2023. [Paper]
Loss-driven methods
Perceptual generative adversarial networks for small object detection, CVPR 2017. [Paper]
Mimicking very efficient network for object detection, CVPR 2017. [Paper]
Fused discriminative metric learning for low resolution pedestrian detection, ICIP 2017. [Paper]
Boosted convolutional neural networks (bcnn) for pedestrian detection, WACV 2017. [Paper]
Subcategory-aware convolutional neural networks for object proposals and detection, WACV 2017. [Paper]
Repulsion loss: Detecting pedestrians in a crowd, CVPR 2018. [Paper]
Learning lightweight pedestrian detector with hierarchical knowledge distillation, ICIP 2019. [Paper]
Discriminative feature transformation for occluded pedestrian detection, ICCV 2019. [Paper]
Count- and Similarity-aware R-CNN for Pedestrian Detection, ECCV 2020. [Paper]
Which to Match? Selecting Consistent GT-Proposal Assignment for Pedestrian Detection, ArXiv 2021. [Paper]
LLA: Loss-aware Label Assignment for Dense Pedestrian Detection, ArXiv 2021. [Paper]
Pedestrian Detection by Exemplar-Guided Contrastive Learning, ArXiv 20201. [Paper]
Occluded Pedestrian Detection via Distribution-Based Mutual-Supervised Feature Learning, TITS 2021. [Paper]
VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision, CVPR 2023. [Paper]
Post-processing methods
End-to-end people detection in crowded scenes, CVPR 2016. [Paper]
Led: Localization-quality estimation embedded detector, ICIP 2018. [Paper]
Learning to separate: Detecting heavily-occluded objects in urban scenes, arXiv 2019. [Paper]
Single shot multibox detector with kalman filter for online pedestrian detection in video, IEEE Access 2019. [Paper]
Adaptive nms: Refining pedestrian detection in a crowd, CVPR 2019. [Paper]
S3d: Scalable pedestrian detection via score scale surface discrimination, TCSVT 2020. [Paper]
Nms by representative region: Towards crowded pedestrian detection by proposal pairing, CVPR 2020. [Paper]
NOH-NMS: Improving Pedestrian Detection by Nearby Objects Hallucination, ACM-MM 2020. [Paper]
DETR for Pedestrian Detection, Arxiv 2020. [Paper]
NMS-Loss: Learning with Non-Maximum Suppression for Crowded Pedestrian Detection, ICMR 2021. [Paper]
Pedestrian Detection for Autonomous Cars: Inference Fusion of Deep Neural Networks, IEEE TITS 2022. [Paper]
Region NMS-based deep network for gigapixel level pedestrian detection with two-step cropping, Neurocomputing 2022. [Paper]
OTP-NMS: Toward Optimal Threshold Prediction of NMS for Crowded Pedestrian Detection, IEEE TIP2023. [Paper]
Neural Attention-Driven Non-Maximum Suppression for Person Detection, TIP2023. [Paper]
Multi-task methods
What can help pedestrian detection? CVPR 2017. [Paper]
Accurate pedestrian detection by human pose regression, TIP 2019. [Paper]
Human detection aided by deeply learned semantic masks, TCSVT 2019. [Paper]
Cluenet: A deep framework for occluded pedestrian pose estimation, BMVC 2019. [Paper]
Semantic part rcnn for real-world pedestrian detection, CVPRW 2019. [Paper]
Re-id driven localization refinement for person search, ICCV 2019. [Paper]
PEN: Pose-embedding network for pedestrian detection, TCSVT 2020. [Paper]
A unified multi-task learning architecture for fast and accurate pedestrian detection, TITS 2020. [Paper]
Enhanced Multi-Task Learning Architecture for Detecting Pedestrian at Far Distance, TITS 2022. [Paper]
Detachable Crowd Density Estimation Assisted Pedestrian Detection, TITS 2023. [Paper]
Urban scene based Semantical Modulation for Pedestrian Detection, Neurocomputing 2022. [Paper]
Generalization
Generalizable Pedestrian Detection: The Elephant In The Room, CVPR 2021. [Paper]
Pedestrian Detection: Domain Generalization, CNNs, Transformers and Beyond, arXiv 2022. [Paper]
Source-Free Unsupervised Cross-Domain Pedestrian Detection via Pseudo Label Mining and Screening, ICME 2022. [Paper]
others
Exploiting target data to learn deep convolutional networks for scene-adapted human detection, TIP 2018. [Paper]
Deep learning approaches on pedestrian detection in hazy weather, TIE 2019. [Paper]
Pedestrian detection from thermal images using saliency maps, CVPRW 2019. [Paper]
Domainadaptive pedestrian detection in thermal images, ICIP 2019. [Paper]
Spatial focal loss for pedestrian detection in fisheye imagery, WACV 2019.[Paper]
Oriented spatial transformer network for pedestrian detection using fish-eye camera, TMM 2020. [Paper]
Semi-supervised human detection via region proposal networks aided by verification, TIP 2020. [Paper]
Task-conditioned Domain Adaptation for Pedestrian Detection in Thermal Imagery, ECCV 2020. [Paper]
Self-bootstrapping pedestrian detection in downward-viewing fisheye cameras using pseudo-labeling, ICME 2020. [Paper]
Joint pedestrian detection and risk-level prediction with motion-representation-by-detection, ICRA 2020. [Paper]
Adversarial training-based hard example mining for pedestrian detection in fish-eye images, TITS 2020. [Paper]
Segmentation-Based Bounding Box Generation for Omnidirectional Pedestrian Detection, CVIU 2021. [Paper]
Unreliable-to-Reliable Instance Translation for Semi-Supervised Pedestrian Detection, TMM 2021. [Paper]
Real-time and Accurate UAV Pedestrian Detection for Social Distancing Monitoring in COVID-19 Pandemic, TMM 2021. [Paper]
Radio-Assisted Human Detection, TMM 2022. [Paper]
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes, CVPR 2022. [Paper]
Accurate and Real-Time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network, IEEE RAL 2023. [Paper]
PEDRo: an Event-based Dataset for Person Detection in Robotics, CVPRW2023. [Paper]
NIRPed: A Novel Benchmark for Nighttime Pedestrian and Its Distance Joint Detection, TITS2023. [Paper]
Multispectral deep neural networks for pedestrian detection, BMVC 2016. [Paper]
Fully convolutional region proposal networks for multispectral person detection, CVPR 2017. [Paper]
Pedestrian detection for autonomous vehicle using multi-spectral cameras, TIV 2019. [Paper]
Fusion of multispectral data through illuminationaware deep neural networks for pedestrian detection, IF 2019. [Paper]
Illuminationaware faster r-cnn for robust multispectral pedestrian detection, PR 2019. [Paper]
Cross-modality interactive attention network for multispectral pedestrian detection, IF 2019. [Paper]
Improving Multispectral Pedestrian Detection by Addressing Modality Imbalance Problems, ECCV 2020. [Paper]
Spatio-Contextual Deep Network Based Multimodal Pedestrian Detection For Autonomous Driving, arXiv 2021. [Paper]
Guided Attentive Feature Fusion for Multispectral Pedestrian Detection, WACV 2021. [Paper]
Uncertainty-Guided Cross-Modal Learning for Robust Multispectral Pedestrian Detection, TCSVT 2021. [Paper]
Deep Cross-Modal Representation Learning and Distillation for Illumination-Invariant Pedestrian Detection, TCSVT 2022. [Paper]
Spatio-Contextual Deep Network Based Multimodal Pedestrian Detection For Autonomous Driving, TITS 2021. [Paper]
BAANet: Learning Bi-directional Adaptive Attention Gates for Multispectral Pedestrian Detection, ArXiv 2021. [Paper]
Confidence-aware Fusion using Dempster-Shafer Theory for Multispectral Pedestrian Detection, TMM 2022. [Paper]
Multispectral interaction convolutional neural network for pedestrian detection, CVIU 2022. [Paper]
Locality guided cross-modal feature aggregation and pixel-level fusion for multispectral pedestrian detection, Information Fusion 2022. [Paper]
Learning a Dynamic Cross-Modal Network for Multispectral Pedestrian Detection, ACMMM 2022. [Paper]
Multiscale Cross-modal Homogeneity Enhancement and Confidence-aware Fusion for Multispectral Pedestrian Detection, TMM 2023. [Paper]
If this project help your research, please consider to cite our survey paper.
@article{Cao_PDR_TPAMI_2020,
author = {Jiale Cao and Yanwei Pang and Jin Xie and Fahad Shahbaz Khan and Ling Shao},
title = {From Handcrafted to Deep Features for Pedestrian Detection: A Survey},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {44},
number = {9},
year = {2022},
pages = {4913-4934},
}
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