Pedestrian Detection
113 papers with code • 6 benchmarks • 15 datasets
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 )
Benchmarks
These leaderboards are used to track progress in Pedestrian Detection
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Libraries
Use these libraries to find Pedestrian Detection models and implementationsDatasets
CityPersons
PRW
ETH
LLVIP
INRIA Person
TJU-DHD
CADP
EuroCity Persons
RailEye3D Dataset
Most implemented papers
Multispectral Deep Neural Networks for Pedestrian Detection
Multispectral pedestrian detection is essential for around-the-clock applications, e. g., surveillance and autonomous driving.
CityPersons: A Diverse Dataset for Pedestrian Detection
aibeedetect/bfjdet
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CVPR 2017
Convnets have enabled significant progress in pedestrian detection recently, but there are still open questions regarding suitable architectures and training data.
Learning Cross-Modal Deep Representations for Robust Pedestrian Detection
Then, the learned feature representations are transferred to a second deep network, which receives as input an RGB image and outputs the detection results.
Accurate Single Stage Detector Using Recurrent Rolling Convolution
In this paper, we proposed a novel single stage end-to-end trainable object detection network to overcome this limitation.
Illuminating Pedestrians via Simultaneous Detection & Segmentation
When placed properly, the additional supervision helps guide features in shared layers to become more sophisticated and helpful for the downstream pedestrian detector.
Repulsion Loss: Detecting Pedestrians in a Crowd
bailvwangzi/repulsion_loss_ssd
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CVPR 2018
In this paper, we first explore how a state-of-the-art pedestrian detector is harmed by crowd occlusion via experimentation, providing insights into the crowd occlusion problem.
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond
yueruchen/Pedestrian-Synthesis-GAN
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The results show that our framework can smoothly synthesize pedestrians on background images of variations and different levels of details.
Center and Scale Prediction: Anchor-free Approach for Pedestrian and Face Detection
Like edges, corners, blobs and other feature detectors, the proposed detector scans for feature points all over the image, for which the convolution is naturally suited.
Occluded Prohibited Items Detection: an X-ray Security Inspection Benchmark and De-occlusion Attention Module
Furthermore, to deal with the occlusion in X-ray images detection, we propose the De-occlusion Attention Module (DOAM), a plug-and-play module that can be easily inserted into and thus promote most popular detectors.
From Handcrafted to Deep Features for Pedestrian Detection: A Survey
In addition to single-spectral pedestrian detection, we also review multi-spectral pedestrian detection, which provides more robust features for illumination variance.
