Browse SoTA > Computer Vision > Autonomous Vehicles > Pedestrian Detection

Pedestrian Detection

28 papers with code · Computer Vision
Subtask of Autonomous Vehicles

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 )

Leaderboards

Greatest papers with code

Fast Algorithms for Convolutional Neural Networks

CVPR 2016 XiaoMi/mace

The algorithms compute minimal complexity convolution over small tiles, which makes them fast with small filters and small batch sizes.

PEDESTRIAN DETECTION SELF-DRIVING CARS

Gliding vertex on the horizontal bounding box for multi-oriented object detection

21 Nov 2019xuannianz/EfficientDet

Yet, the widely adopted horizontal bounding box representation is not appropriate for ubiquitous oriented objects such as objects in aerial images and scene texts.

OBJECT DETECTION IN AERIAL IMAGES PEDESTRIAN DETECTION SCENE TEXT SCENE TEXT DETECTION

Joint Detection and Identification Feature Learning for Person Search

CVPR 2017 ShuangLI59/person_search

Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates.

PEDESTRIAN DETECTION PERSON RE-IDENTIFICATION PERSON SEARCH

A Unified Multi-scale Deep Convolutional Neural Network for Fast Object Detection

25 Jul 2016zhaoweicai/mscnn

A unified deep neural network, denoted the multi-scale CNN (MS-CNN), is proposed for fast multi-scale object detection.

FACE DETECTION PEDESTRIAN DETECTION REAL-TIME OBJECT DETECTION

Accurate Single Stage Detector Using Recurrent Rolling Convolution

CVPR 2017 xiaohaoChen/rrc_detection

In this paper, we proposed a novel single stage end-to-end trainable object detection network to overcome this limitation.

3D OBJECT DETECTION PEDESTRIAN DETECTION

Repulsion Loss: Detecting Pedestrians in a Crowd

CVPR 2018 bailvwangzi/repulsion_loss_ssd

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.

#4 best model for Pedestrian Detection on Caltech (using extra training data)

PEDESTRIAN DETECTION

Pedestrian Detection: The Elephant In The Room

19 Mar 2020hasanirtiza/Pedestron

Through this study, we find that existing state-of-the-art pedestrian detectors generalize poorly from one dataset to another.

 SOTA for Pedestrian Detection on CityPersons (using extra training data)

AUTONOMOUS DRIVING PEDESTRIAN DETECTION

Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters

CVPR 2017 huangshiyu13/RPNplus

Such "in-the-tail" data is notoriously hard to observe, making both training and testing difficult.

PEDESTRIAN DETECTION

Learning Cross-Modal Deep Representations for Robust Pedestrian Detection

CVPR 2017 SoonminHwang/rgbt-ped-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.

PEDESTRIAN DETECTION

Multispectral Deep Neural Networks for Pedestrian Detection

8 Nov 2016SoonminHwang/rgbt-ped-detection

Multispectral pedestrian detection is essential for around-the-clock applications, e. g., surveillance and autonomous driving.

AUTONOMOUS DRIVING PEDESTRIAN DETECTION