Image Segmentation - Groups

RRSIS

Referring Remote Sensing Image Segmentation (RRSIS) is a new challenge that combines computer vision and natural language processing, delineating specific regions in aerial...

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RRSIS-D

Referring Remote Sensing Image Segmentation (RRSIS) is a new challenge that combines computer vision and natural language processing, delineating specific regions in aerial...

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Open-vocabulary image segmentation

Open-vocabulary image segmentation explores how to recognize any categories at pixel level.

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TGS Salt Identification Challenge

The dataset used for this project contains 4,000 seismic images with 4,000 labeled mask images. The seismic images are in grayscale, and the mask images are in black and white.

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Pascal VOC Challenge

The Pascal VOC Challenge dataset is a benchmark for object detection and image segmentation.

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Berkeley Segmentation Dataset (BSDS)

Contour detection and hierarchical image segmentation.

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CATCH dataset

The CATCH dataset is used to test the proposed Style-Extracting Diffusion Models (STEDM) for canine cancer histology image segmentation.

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HER2 dataset

The HER2 dataset is used to test the proposed Style-Extracting Diffusion Models (STEDM) for histopathology image segmentation.

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MRSpineSeg Challenge

The MRSSegClg dataset is used for external testing of the proposed method.

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MIT-Adobe FiveK

The MIT-Adobe FiveK dataset, a large-scale dataset for image segmentation and object detection.

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SAMRS

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

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OPTIMA cyst segmentation challenge (OCSC) dataset

The OPTIMA cyst segmentation challenge (OCSC) dataset analyzed in this work contains OCT image stacks acquired by a variety of imaging vendors.

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OCSC dataset

The OCSC dataset contains OCT image stacks acquired by a variety of imaging vendors, where, each image is manually annotated by two manual graders/annotators.

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Neounet: Towards accurate colon in Ad-polyp segmentation and neoplasm detection

Neounet: Towards accurate colon in Ad-polyp segmentation and neoplasm detection.

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Wm-dova maps for accurate polyp highlighting in colonoscopy

Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs. saliency maps from physicians.

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Synthia

The Synthia dataset is a large-scale urban scene understanding dataset, containing 9000 samples. It is used for semantic segmentation tasks.

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PASCAL-5i

Few-shot segmentation remains challenging due to the limitations of its labeling information for unseen classes. Most previous approaches rely on extracting high-level feature...

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GTA

The GTA dataset consists of 24966 synthetic images synthetically generated from a video game consisting of outdoor scenes with rich variety of variations in lighting and trafﬁc...

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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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Breast Ultrasound Scan Images (BUSI)

Dataset of breast ultrasound images for image segmentation tasks.

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260 datasets found