feature-pyramid-network
There are 19 repositories under feature-pyramid-network topic.
unsky/FPN
Feature Pyramid Networks for Object Detection
haofengac/MonoDepth-FPN-PyTorch
Single Image Depth Estimation with Feature Pyramid Network
gasparian/multiclass-semantic-segmentation
Experiments with UNET/FPN models and cityscapes/kitti datasets [Pytorch]
simonmeister/motion-rcnn
Motion R-CNN: Mask R-CNN with support for 3D motion estimation (prototype)
EmGarr/kerod
DETR - Faster RCNN implementation in tensorflow 2
AdeelH/pytorch-fpn
PyTorch implementations of some FPN-based semantic segmentation architectures: vanilla FPN, Panoptic FPN, PANet FPN; with ResNet and EfficientNet backbones.
yuhuan-wu/RDPNet
(IEEE TIP 2021) Regularized Densely-connected Pyramid Network for Salient Instance Segmentation
stnamjef/feature_pyramid_network
Feature Pyramid Network based on VGG16 and ResNet101
D0352276/SFPN-Synthetic-FPN-for-Object-Detection
The SFPN is a novel plug-and-play component for the CNN object detector. This project is the official code for the paper "SFPN: Synthetic FPN for Object Detection" in IEEE ICIP 2022.
001honi/video-processing
Digital Video Processing Graduate Course Homeworks
ALLARDLE/ShipSARDetect_mmdetection
Project on the implementation of deep-learning models for ship detection on SAR images.
edaaydinea/Low-Grade-Glioma-Segmentation
This is a capstone project on a real dataset related to segmenting low-grade glioma. This capstone project is included in the UpSchool Machine Learning & Deep Learning Program in partnership with Google Developers.
film-net/film-net.github.io
Website of "FILM: Frame Interpolation for Large Motion", In ECCV 2022.
Ziruiwang409/improved-faster-rcnn
Object Detector for Autonomous Vehicles Based on Improved Faster-RCNN
SomeoneDistant/Optical-Flow-Estimation-in-Foggy-Scenes
Improve performance of PWC-Net in foggy scenes
pigtamer/mx_fpn
An implementation for fpn network with mxnet
prathmeshlonkar10/Celestial-object-recognition-using-Feature-Pyramid-Network
Project to recognize STAR presence in an image and build a bounding box around it, if identified