RetinaNet — Torchvision main documentation
The RetinaNet model is based on the Focal Loss for Dense Object Detection paper. The detection module is in Beta stage, and backward compatibility is not guaranteed. The following model builders …
[1708.02002] Focal Loss for Dense Object Detection - arXiv.org
Aug 7, 2017 · Our results show that when trained with the focal loss, RetinaNet is able to match the speed of previous one-stage detectors while surpassing the accuracy of all existing state-of-the-art …
GitHub - yhenon/pytorch-retinanet: Pytorch implementation of RetinaNet …
Pytorch implementation of RetinaNet object detection as described in Focal Loss for Dense Object Detection by Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He and Piotr Dollár.
How RetinaNet works? | ArcGIS API for Python | Esri Developer
RetinaNet is one of the best one-stage object detection models that has proven to work well with dense and small scale objects. For this reason, it has become a popular object detection model to be used …
Object Detection with RetinaNet - Keras
May 17, 2020 · RetinaNet uses a feature pyramid network to efficiently detect objects at multiple scales and introduces a new loss, the Focal loss function, to alleviate the problem of the extreme …
PyTorch RetinaNet: A Comprehensive Guide - codegenes.net
Nov 14, 2025 · RetinaNet, introduced by Facebook AI Research (FAIR) in 2017, is a one-stage object detection algorithm that addresses the problem of class imbalance during training, which is a …
RetinaNet Model for object detection explanation
Facebook AI research (FAIR ) team has introduced RetinaNet model with aim to tackle dense and small objects detection problem. For this reason, it has become a popular object detection model that one …
RetinaNet: The beauty of Focal Loss | Towards Data Science
May 12, 2021 · To summarize, RetinaNet made a significant improvement to the Object detection field when it was launched. The idea that a one-stage detector outperforming a two-stage detector was …
RetinaNet: Fast and Accurate Object Detection Model - Viso
Apr 17, 2024 · The RetinaNet model is a one-stage object detection model incorporating features such as Focal Loss, a Feature Pyramid Network (FPN), and various architectural improvements. These …
RetinaNet Model Architecture - OpenGenus IQ
RetinaNet is a one-stage object detection model that addresses the challenges of imbalanced data and objects of different sizes. It accomplishes this through a unique architecture that uses a Feature …