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Jingtao Zhong's Projects

attention-gated-networks icon attention-gated-networks

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

attentiongan icon attentiongan

AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation

biggan-pytorch icon biggan-pytorch

The author's officially unofficial PyTorch BigGAN implementation.

chatpaper icon chatpaper

Use ChatGPT to summarize the arXiv papers. 全流程加速科研,利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复

crack_segmentation icon crack_segmentation

This repository contains code and dataset for the task crack segmentation using two architectures UNet_VGG16, UNet_Resnet and DenseNet-Tiramusu

crackseg9k icon crackseg9k

[ECCV W 2022] "CrackSeg9k: A Collection and Benchmark for Crack Segmentation Datasets and Frameworks" by Shreyas Kulkarni, Shreyas Singh, Dhananjay Balakrishnan, Siddharth Sharma, Saipraneeth Devunuri, Sai Chowdeswara Rao Korlapati.

cssr icon cssr

Crack Segmentation for Low-Resolution Images using Joint Learning with Super-Resolution (CSSR) was accepted to international conference on MVA2021 (oral), and selected for the Best Practical Paper Award.

deepcrack icon deepcrack

DeepCrack: Learning Hierarchical Convolutional Features for Crack Detection

detectron2 icon detectron2

Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.

esrgan icon esrgan

ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.

keras-dcgan icon keras-dcgan

Keras implementation of Deep Convolutional Generative Adversarial Networks

mask-rcnn-tf2 icon mask-rcnn-tf2

这是一个mask-rcnn-tf2的库,可以用于训练自己的模型。

mask_rcnn icon mask_rcnn

Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

monodepth2 icon monodepth2

[ICCV 2019] Monocular depth estimation from a single image

paddleseg icon paddleseg

End-to-end image segmentation kit based on PaddlePaddle.

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