Image Segmentation - Groups

MSDU-net: A Multi-Scale Dilated U-net for Blur Detection

Blur detection is the separation of blurred and clear regions of an image, which is an important and challenging task in computer vision. In this work, we regard blur detection...

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PASCAL Context

The PASCAL Context dataset is a benchmark for multi-task learning in computer vision. It contains 10103 images with 5 tasks: semantic segmentation, human body part segmentation,...

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ISIC skin cancer segmentation challenge and lung segmentation dataset

Skin cancer segmentation and lung lesion segmentation datasets

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OneFormer

OneFormer is a universal image segmentation framework jointly trained on the panoptic, semantic, and instance segmentation tasks.

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Pascal Voc 2012 and Cityscapes

The dataset used in the paper is Pascal Voc 2012 and Cityscapes.

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PASCAL-Context Dataset

The PASCAL-Context dataset comprises 4,998 images for training and 5,105 images for testing. This dataset offers dense labels for four tasks including semantic segmentation,...

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Task-Aware Low-Rank Adaptation of Segment Anything Model

The Segment Anything Model (SAM) has been proven to be a powerful foundation model for image segmentation tasks, which is an important task in computer vision. However, the...

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LVIS: A dataset for segment anything model (SAM)

A dataset for segment anything model (SAM) to evaluate its performance.

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MobileSAMv2: Faster Segment Anything to Everything

Segment anything model (SAM) addresses two practical yet challenging segmentation tasks: segment anything (SegAny), which utilizes a certain point to predict the mask for a...

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FloodNet

FloodNet is a high-resolution image dataset acquired by a small UAV platform, DJI Mavic Pro quadcopters, after Hurricane Harvey.

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OCR dataset

The OCR dataset is a dataset of handwritten digits, each image is an 8x16 binary image, and there are 52152 samples in total.

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LVIS-92i

The LVIS-92i dataset contains 92 images with 92 object categories.

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PACO-Part

The PACO-Part dataset contains 59 images with 59 object categories.

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PerSeg

The PerSeg dataset contains 40 images with 40 object categories.

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CamVid

The dataset used in the paper is a pre-trained ResNet-50 classiﬁer, which is used for image synthesis, unpaired image-to-image translation, and feature similarity estimation.

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PASCAL-Part

PASCAL-Part is a dataset for semantic part segmentation. It contains images of cars and horses with annotated part segmentation masks.

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Synthetic Data

The dataset used in the paper is a synthetic dataset for off-policy contextual bandits, with contexts x ∈ X, a finite set of actions A, and bounded real rewards r ∈ A → [0, 1].

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PASCAL

A dataset of textual entailment tasks, used for evaluating the ability of language models to understand relationships between texts.

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Laryngeal Dataset for Comparative Study on CNN Based Semantic Segmentation

A novel dataset of laryngeal endoscopic images with ground truth segmentation maps for comparative study on CNN-based semantic segmentation.

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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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246 datasets found