Image Segmentation - Groups

ISPRS 2D semantic labeling benchmark (Vaihingen)

The ISPRS 2D semantic labeling benchmark (Vaihingen) dataset is used for evaluating the proposed method.

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LoveDA dataset

The LoveDA dataset consists of 5,987 high-quality optical remote sensing images with a resolution of 0.3 meters per pixel.

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Vaihingen dataset

The Vaihingen dataset consists of 1440 scenes with a size of 250×250 pixels. Each scene is a colour-infrared (CIR) true orthophoto and a height grid (digital surface model; DSM)...

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SAMRS

SAMRS: Scaling-up remote sensing segmentation dataset with segment anything model

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Vegetation change assessment in satellite imagery

Vegetation change assessment in satellite imagery using U-net super-neural segmentation and similarity calculation

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Inria Aerial Image Labeling Data Set

Semantic segmentation in high resolution remote sensing images

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ISPRS Potsdam Semantic Labeling data set

Semantic segmentation in high resolution remote sensing images

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Geomatics and Computer Vision/Datasets

The dataset used in this study consists of multiple aerial and satellite datasets, including UAV, Airborne, and Satellite data.

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SkySat ESA archive

The dataset used in this study consists of multiple aerial and satellite datasets, including UAV, Airborne, and Satellite data.

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Implicit ray-transformers for multi-view remote sensing image segmentation

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Remote-sensing image segmentation based on implicit 3-d scene representation

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Multi-view segmentation in Remote Sensing (RS) scenes

Multi-view segmentation in Remote Sensing (RS) seeks to segment images from diverse perspectives within a scene.

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Gaofen dataset

The Gaofen dataset is a high-quality PolSAR semantic segmentation dataset.

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CITY-OSM

CITY-OSM dataset includes Berlin and Potsdam in Germany, Chicago in the United States, Paris in France, Zurich in Switzerland and Tokyo in Japan, with a total of 1641 aerial...

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Private Dataset

A private dataset of UAV-borne remote sensing images with a resolution between 10000×10000 and 20000×20000 is constructed. Each remote sensing image which corresponds to the red...

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Samba: Semantic Segmentation of Remotely Sensed Images with State Space Model

High-resolution remotely sensed images pose a challenge for commonly used semantic segmentation methods such as Convolutional Neural Network (CNN) and Vision Transformer (ViT).