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AATTCT-IDS
A benchmark Abdominal Adipose Tissue CT Image Dataset (AATTCT-IDS) for image denoising, semantic segmentation, and radiomics evaluation. -
RueMonge2014
The dataset used in this paper for 3D point cloud classification and semantic segmentation tasks. -
TUM-MLS-2016
TUM-MLS-2016: An annotated mobile LiDAR dataset of the TUM City Campus for semantic point cloud interpretation in urban areas. -
ImageNet, CIFAR-10, and Cityscapes
The dataset used in this paper is ImageNet and CIFAR-10 for image classification, and Cityscapes for semantic segmentation. -
Cityscapes dataset for semantic urban scene understanding
The Cityscapes dataset is a large-scale urban scene dataset containing over 25,000 images. -
2D-3D-S dataset
The 2D-3D-S dataset is an indoor dataset with multiple modalities from 2D, 2.5D and 3D domains, with instance-level semantic and geometric annotations. -
ModelNet-10
The ModelNet-10 dataset is a benchmark for 3D point cloud classification and semantic segmentation. It contains 4,899 untextured CAD models divided into 10 categories. -
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... -
ImageNet-1K, ADE20K, and COCO 2017
The dataset used in the paper is ImageNet-1K, ADE20K, and COCO 2017. -
COCO Stuff
COCO Stuff dataset is an extension of the COCO dataset, 164,000 images covering 171 classes are annotated with segmentation masks. -
ScanNet-v2
Learning from bounding-boxes annotations has shown great potential in weakly-supervised 3D point cloud instance segmentation. However, we observed that existing methods would... -
Pyramid scene parsing network
Pyramid scene parsing network for semantic segmentation. -
Laplacian Pyramid Reconstruction Network
Laplacian Pyramid Reconstruction Network for semantic segmentation. -
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
Semantic segmentation requires both rich spatial information and sizeable receptive field. However, modern approaches usually compromise spatial resolution to achieve real-time... -
Few-shot semantic segmentation via prototype augmentation with image-level an...
Few-shot semantic segmentation via prototype augmentation with image-level annotations -
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... -
DABNet for Real-time Semantic Segmentation
The proposed Depth-wise Asymmetric Bottleneck Network (DABNet) is designed for real-time semantic segmentation. It uses a novel Depth-wise Asymmetric Bottleneck (DAB) module to... -
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,...
