| Localized Semantic Feature Mixers for Efficient Pedestrian Detection in Autonomous Driving | | 0.87 | 19.5 | LSFM | 2023-01-01 |
| F2DNet: Fast Focal Detection Network for Pedestrian Detection | ✓ Link | 1.71 | 20.42 | F2DNet (extra data) | 2022-03-04 |
| Generalizable Pedestrian Detection: The Elephant In The Room | ✓ Link | 1.76 | 25.7 | Pedestron | 2020-03-19 |
| F2DNet: Fast Focal Detection Network for Pedestrian Detection | ✓ Link | 2.2 | 38.7 | F2DNet | 2022-03-04 |
| VLPD: Context-Aware Pedestrian Detection via Vision-Language Semantic Self-Supervision | ✓ Link | 2.3 | 37.7 | VLPD | 2023-04-06 |
| NMS-Loss: Learning with Non-Maximum Suppression for Crowded Pedestrian Detection | ✓ Link | 2.92 | | NMS-Loss | 2021-06-04 |
| CrowdHuman: A Benchmark for Detecting Human in a Crowd | ✓ Link | 3.46 | | FRCNN+FPN-Res50+refined feature map+Crowdhuman | 2018-04-30 |
| Center and Scale Prediction: Anchor-free Approach for Pedestrian and Face Detection | ✓ Link | 3.8 | | CSP + CityPersons dataset | 2019-04-05 |
| Repulsion Loss: Detecting Pedestrians in a Crowd | ✓ Link | 4.0 | | RepLoss + CityPersons dataset | 2017-11-21 |
| Occlusion-aware R-CNN: Detecting Pedestrians in a Crowd | | 4.1 | | OR-CNN + CityPersons dataset | 2018-07-23 |
| Center and Scale Prediction: Anchor-free Approach for Pedestrian and Face Detection | ✓ Link | 4.5 | | CSP | 2019-04-05 |
| Learning Efficient Single-stage Pedestrian Detectors by Asymptotic Localization Fitting | ✓ Link | 4.5 | | ALFNet + CityPersons dataset | 2018-09-01 |
| Repulsion Loss: Detecting Pedestrians in a Crowd | ✓ Link | 5.0 | | RepLoss | 2017-11-21 |
| CityPersons: A Diverse Dataset for Pedestrian Detection | ✓ Link | 5.1 | | Zhang et al. * | 2017-02-19 |
| What Can Help Pedestrian Detection? | | 5.5 | | HyperLearner | 2017-05-08 |
| CityPersons: A Diverse Dataset for Pedestrian Detection | ✓ Link | 5.8 | | Zhang et al. | 2017-02-19 |
| Learning Efficient Single-stage Pedestrian Detectors by Asymptotic Localization Fitting | ✓ Link | 6.1 | | ALFNet | 2018-09-01 |
| Temporal-Context Enhanced Detection of Heavily Occluded Pedestrians | | 6.5 | | TFAN | 2020-06-01 |
| Is Faster R-CNN Doing Well for Pedestrian Detection? | | 7.3 | | RPN+BF | 2016-07-24 |
| Illuminating Pedestrians via Simultaneous Detection & Segmentation | ✓ Link | 7.36 | | SDS-RCNN | 2017-06-26 |
| Fused DNN: A deep neural network fusion approach to fast and robust pedestrian detection | | 8.18 | | F-DNN+SS | 2016-10-11 |
| Is Faster R-CNN Doing Well for Pedestrian Detection? | | 8.7 | | FasterRCNN | 2016-07-24 |
| Scale-aware Fast R-CNN for Pedestrian Detection | | 9.68 | | SA-FastRCNN | 2015-10-28 |
| A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection | ✓ Link | 9.95 | | MS-CNN | 2016-07-25 |
| Learning Multilayer Channel Features for Pedestrian Detection | | 10.40 | | MCF | 2016-03-01 |
| Learning Complexity-Aware Cascades for Deep Pedestrian Detection | | 11.75 | | CompACT-Deep | 2015-07-19 |
| Part-Level Convolutional Neural Networks for Pedestrian Detection Using Saliency and Boundary Box Alignment | ✓ Link | 12.4 | | Part-level CNN + saliency and bounding box alignment | 2018-10-01 |
| Pedestrian Detection Inspired by Appearance Constancy and Shape Symmetry | | 16.20 | | NNNF | 2015-11-25 |
| Filtered Channel Features for Pedestrian Detection | | 17.1 | | Checkerboards+ | 2015-01-23 |
| Pedestrian Detection aided by Deep Learning Semantic Tasks | | 20.9 | | TA-CNN | 2014-11-29 |
| Taking a Deeper Look at Pedestrians | | 23.3 | | AlexNet | 2015-01-23 |
| Local Decorrelation For Improved Pedestrian Detection | | 24.8 | | LDCF | 2014-12-01 |
| UniHCP: A Unified Model for Human-Centric Perceptions | ✓ Link | | 27.2 | UniHCP (FT) | 2023-03-06 |