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Search results for dataset deeplab
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deeplab
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17 search results found
Deeplab_v3
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797
Tensorflow Implementation of the Semantic Segmentation DeepLab_V3 CNN
Tensorflow Deeplab V3 Plus
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637
DeepLabv3+ built in TensorFlow
Portrait Segmentation
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310
Real-time portrait segmentation for mobile devices
Bdl
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185
Vip Deeplab
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149
Deeplayout
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114
Deep learning based page layout analysis
Mobile Deeplab V3 Plus
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95
Deeplab-V3+ model with MobilenetV2/MobilenetV3 on TensorFlow for mobile deployment.
Deeplab V3 Plus Cityscapes
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87
mIOU=80.02 on cityscapes. My implementation of deeplabv3+ (also know as 'Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation' based on the dataset of cityscapes).
Unsupervised_llamas
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65
Code for https://unsupervised-llamas.com
Segmentation_pytorch
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54
semantic segmentation pytorch 语义分割
Pspnet Cudnn5
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39
The PSPNET supported cudnn v.5 based on https://github.com/hszhao/PSPNet
Deeplabv3plus_on_mapillary_vistas
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30
Semantic Segmentation on the Mapillary Vistas Dataset
Grapy Ml
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30
(AAAI2020)Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Tf Keras Deeplabv3p Model Set
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24
end-to-end DeepLab V3+ semantic segmentation pipeline, implemented with tf.keras
Deeplab Large Fov
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21
My Implementation of the deeplab_v1 (known as deeplab large fov)
Pathonet
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19
Deeplabv3 Tf2.0
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18
This project implements the SOTA image segmentation algorithm deeplab V3+ with tensorflow 2.0
Synthetic Video Generation For Autonomous Cars
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11
A huge challenge for autonomous vehicles(ACs) is to have a dataset that captures real-world multitudinous driving conditions. The currently available video datasets are not annotated & most of them aren't high resolution videos which is again an impediment for object detection. I am excited to solve this problem by annotating & generating photo-realistic synthetic video dataset for ACs using DeepLab, conditional GANs.
Pytorch_deeplab
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9
Here is an implementation of DeepLabv3+ in PyTorch(1.7). It supports many backbones and datasets.
Weakly Sup Crackdet
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7
Repo for ICPR2020 paper "Crack Detection as a Weakly-Supervised Problem: Towards Achieving Less Annotation-Intensive Crack Detectors"
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