Image Segmentation - Groups

RefCOCO

The dataset used in the paper is a benchmark for referring expression grounding, containing 142,210 referring expressions for 50,000 referents in 19,994 images.

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AFHQ

The dataset used in the paper is a set of images from the AFHQ dataset, containing 1.5K images of different animal faces.

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Cityscapes Panoptic Segmentation

The Cityscapes dataset consists of 8 thing classes and 11 stuff classes.

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NYUv2

Multi-task learning (MTL) research is broadly divided into two categories: one is to learn the correlation between tasks through model structures, and the other is to balance...

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xView2: 1st place solution

A dataset for assessing building damage from satellite imagery

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Singapore Whole-sky IMaging CATegories (SWIMCAT)

Singapore Whole-sky IMaging CATegories (SWIMCAT) contains 784 images of five categories: patterned clouds, clear sky, thick dark clouds, veil clouds, and thick white clouds.

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MIT Places2

MIT Places2 is a scene-centric dataset with more than 10 million images consisting of over 400 unique scene classes.

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FGVC Aircraft (Airplanes)

FGVC Aircraft (Airplanes) contains 102 different aircraft model variants with 100 images of each.

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Oxford 102 Flowers

Oxford 102 Flowers is a dataset of images of different flower species.

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Caltech-UCSD Birds (CUB) 200-2011

Caltech-UCSD Birds (CUB) 200-2011 is a frequently used benchmark for unsupervised image segmentation. It consists of 11,788 images from 200 bird species.

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Coco: Common objects in context

Publicly available plant image datasets are crucial in precision agriculture as they reduce the time and eﬀort spent on data collection and preparation. Also, more data enable...

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Syntagen - Harnessing Generative Models for Synthetic Visual Datasets

The dataset is generated using a latent diffusion model, specifically Stable Diffusion 2.1, and is used for semantic segmentation tasks.

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SA-1B

The dataset used in the paper is not explicitly described, but it is mentioned that it is a large-scale medical image segmentation dataset.

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ISPRS Potsdam

The ISPRS Potsdam dataset consists of remotely sensed imagery with a spatial resolution of 5 centimeters, and includes 6 semantic classes.

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AAU-net: An Adaptive Attention U-net for Breast Lesions Segmentation in Ultra...

Three public breast ultrasound datasets (BUSI, Dataset B, and STU) are used to evaluate the segmentation network performance.

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Segment Anything Model

The dataset used in this paper is the Meta Research's Segment Anything Model (SAM) dataset, which consists of images.

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From Image-Level to Pixel-Level Labeling with Convolutional Networks

From image-level to pixel-level labeling with convolutional networks.

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Bitewing Radiography Semantic Segmentation

This dataset is used for semantic segmentation of bitewing radiography images. The goal is to segment the images into caries, enamel, dentin, pulp, crowns, restoration and root...

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Lizard

Multi-class histopathology nuclei analysis tasks, the lack of training data becomes a main bottleneck for the performance of learning-based methods.

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CPM17

The dataset used for histopathology image segmentation and classification.

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246 datasets found