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
Latest papers with no code
Enhancing Multi-View Pedestrian Detection Through Generalized 3D Feature Pulling
The main challenge in multi-view pedestrian detection is integrating view-specific features into a unified space for comprehensive end-to-end perception.
Optimizing Camera Configurations for Multi-View Pedestrian Detection
Jointly considering multiple camera views (multi-view) is very effective for pedestrian detection under occlusion.
Model-agnostic Body Part Relevance Assessment for Pedestrian Detection
Model-agnostic explanation methods for deep learning models are flexible regarding usability and availability.
Low-light Pedestrian Detection in Visible and Infrared Image Feeds: Issues and Challenges
Pedestrian detection has become a cornerstone for several high-level tasks, including autonomous driving, intelligent transportation, and traffic surveillance.
Visible to Thermal image Translation for improving visual task in low light conditions
In this work, an end-to-end framework, which consists of a generative network and a detector network, is proposed to translate RGB image into Thermal ones and compare generated thermal images with real data.
Ranking-based Adaptive Query Generation for DETRs in Crowded Pedestrian Detection
Moreover, to train the rank prediction head better, we propose Soft Gradient L1 Loss.
Comparative study of multi-person tracking methods
The purpose of this study is to discover the techniques used and to provide useful insights about these algorithms in the tracking pipeline that could improve the performance of MOT tracking algorithms.
PSDiff: Diffusion Model for Person Search with Iterative and Collaborative Refinement
Dominant Person Search methods aim to localize and recognize query persons in a unified network, which jointly optimizes two sub-tasks, \ie, pedestrian detection and Re-IDentification (ReID).
PPD: A New Valet Parking Pedestrian Fisheye Dataset for Autonomous Driving
In this paper, wepresent the Parking Pedestrian Dataset (PPD), a large-scale fisheye dataset to support research dealing with real-world pedestrians, especially with occlusions and diverse postures.
Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types
This implies that ML pipelines might not need explicit correction for RS for many object detection applications, but mitigating RS effects in ISP-less ML pipelines that target fine-grained location of the objects may need additional research.
