Semantic Segmentation - Groups

IDD

IDD dataset for Indian Road Scenarios contains 10K frames from 180 videos.

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BDD

Object detection dataset used for training and testing the proposed alert system.

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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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PASCAL Visual Object Classes Challenge

The PASCAL Visual Object Classes Challenge (VOC) is a benchmark dataset for object detection and semantic segmentation.

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Synscapes

The dataset used in the paper is a synthetic dataset for image-based object detection tasks, specifically instance segmentation and monocular 3D detection.

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COCO object detection and instance segmentation, ADE20K semantic segmentation

The dataset used in the paper is the COCO object detection and instance segmentation dataset, and the ADE20K semantic segmentation dataset.

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VOC2012

The VOC2012 dataset is a multi-label image recognition dataset. It contains 11,540 train-val images and 10,991 test images.

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Cityspace

The dataset used for training and testing the proposed RGBD-based obstacle avoidance system for visually impaired people.

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SBD dataset

The SBD dataset is a benchmark dataset for semantic segmentation and object detection.

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COCO 2017 Dataset

The COCO 2017 Dataset is a large-scale benchmark dataset for object detection, semantic segmentation, and instance segmentation.

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CAE v2: Context Autoencoder with CLIP Target

Masked image modeling (MIM) learns visual representation by masking and reconstructing image patches. Applying the reconstruction supervision on the CLIP representation has been...

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CamVid Dataset

CamVid dataset is a benchmark dataset for semantic segmentation. It consists of 700 images with 11 object classes.

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Pascal VOC 2012

The dataset used in the paper is the Pascal VOC 2012 dataset, which is a benchmark for instance segmentation. The dataset consists of 1464 images with 20 class categories and...

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ImageNet-1K, ADE20K, and COCO 2017

The dataset used in the paper is ImageNet-1K, ADE20K, and COCO 2017.

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COCO Stuff

COCO Stuff dataset is an extension of the COCO dataset, 164,000 images covering 171 classes are annotated with segmentation masks.

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ND-MLS dataset

The bottle, grass, cat, and horse datasets were created for semantic segmentation tasks. The datasets contain images of 4 object types. The ND-MLS dataset was evaluated on...

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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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PASCAL VOC 2007

Multi-label image recognition is a practical and challenging task compared to single-label image classification.

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ImageNet, MS COCO, and Pascal VOC datasets

The dataset used in the paper is ImageNet, MS COCO, and Pascal VOC datasets.

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Argoverse-HD, Cityscapes, and nuScenes

The dataset used in the paper is Argoverse-HD, Cityscapes, and nuScenes.

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32 datasets found