Pedestrian Detection
100 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
Focal Loss for Dense Object Detection
facebookresearch/detectron
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ICCV 2017
Our novel Focal Loss focuses training on a sparse set of hard examples and prevents the vast number of easy negatives from overwhelming the detector during training.
Feature Pyramid Networks for Object Detection
PaddlePaddle/PaddleOCR
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CVPR 2017
Feature pyramids are a basic component in recognition systems for detecting objects at different scales.
FCOS: Fully Convolutional One-Stage Object Detection
tianzhi0549/FCOS
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ICCV 2019
By eliminating the predefined set of anchor boxes, FCOS completely avoids the complicated computation related to anchor boxes such as calculating overlapping during training.
Fast Algorithms for Convolutional Neural Networks
XiaoMi/mace
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CVPR 2016
The algorithms compute minimal complexity convolution over small tiles, which makes them fast with small filters and small batch sizes.
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
tinyvision/SOLIDER
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CVPR 2023
Unlike the existing self-supervised learning methods, prior knowledge from human images is utilized in SOLIDER to build pseudo semantic labels and import more semantic information into the learned representation.
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.
Detection in Crowded Scenes: One Proposal, Multiple Predictions
megvii-model/CrowdDetection
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CVPR 2020
We propose a simple yet effective proposal-based object detector, aiming at detecting highly-overlapped instances in crowded scenes.
Multiview Detection with Feature Perspective Transformation
First, how should we aggregate cues from the multiple views?
MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking
We discuss the challenges of creating such a framework, collecting existing and new data, gathering state-of-the-art methods to be tested on the datasets, and finally creating a unified evaluation system.
Joint Detection and Identification Feature Learning for Person Search
Existing person re-identification benchmarks and methods mainly focus on matching cropped pedestrian images between queries and candidates.
