Feature Pyramid Networks for Object Detection
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Updated
May 30, 2018 - Jupyter Notebook
Feature Pyramid Networks for Object Detection
Single Image Depth Estimation with Feature Pyramid Network
Experiments with UNET/FPN models and cityscapes/kitti datasets [Pytorch]
[ECCV 2024] Pytorch code for our ECCV'24 paper NeRF-MAE: Masked AutoEncoders for Self-Supervised 3D Representation Learning for Neural Radiance Fields
Motion R-CNN: Mask R-CNN with support for 3D motion estimation (prototype)
DETR - Faster RCNN implementation in tensorflow 2
PyTorch implementations of some FPN-based semantic segmentation architectures: vanilla FPN, Panoptic FPN, PANet FPN; with ResNet and EfficientNet backbones.
(IEEE TIP 2021) Regularized Densely-connected Pyramid Network for Salient Instance Segmentation
Feature Pyramid Network based on VGG16 and ResNet101
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.
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.
Digital Video Processing Graduate Course Homeworks
Project on the implementation of deep-learning models for ship detection on SAR images.
Object Detector for Autonomous Vehicles Based on Improved Faster-RCNN
Website of "FILM: Frame Interpolation for Large Motion", In ECCV 2022.
Improve performance of PWC-Net in foggy scenes
An implementation for fpn network with mxnet
This repository includes Pytorch implementation of semantic segmentation on aerial image of drone dataset.
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