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CUB200, Cars-196, and Stanford Online Products
The dataset used for experiments on generic image retrieval, person re-identification, and low-shot semantic segmentation. -
ICPC: Instance-Conditioned Prompting with Contrastive Learning for Semantic S...
Semantic segmentation is a fundamental task in computer vision and has witnessed great progress using deep learning in the past few years. It aims at segmenting things or stuff... -
Crack Semantic Segmentation
The proposed framework for crack semantic segmentation. -
Road Semantic Segmentation
The proposed framework for road semantic segmentation. -
PASCAL Visual Object Classes Challenge
The PASCAL Visual Object Classes Challenge (VOC) is a benchmark dataset for object detection and semantic segmentation. -
Incremental learning techniques for semantic segmentation
Incremental learning techniques for semantic segmentation -
SemanticKITTI: A dataset for semantic scene understanding of lidar sequences
SemanticKITTI: A dataset for semantic scene understanding of lidar sequences. -
TORNADO-Net: Multiview Total Variation Semantic Segmentation with Diamond Inc...
Semantic segmentation of point clouds is a key component of scene understanding for robotics and autonomous driving. In this paper, we introduce TORNADO-Net - a neural network... -
Sewer-Culvert Defect Segmentation Dataset
A dataset for sewer-culvert defect segmentation, featuring pixel-level annotations of nine common structural deficiency classes. -
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. -
NYU dataset
The NYU dataset contains 1449 depth maps captured by Kinect. -
SUNCG dataset
The SUNCG dataset is a manually created large-scale synthetic scene dataset. It contains 139368 valid pairs of depth map and complete labels for training, and 470 pairs for... -
ADE20K: A Dataset for Semantic Segmentation
ADE20K: A Dataset for Semantic Segmentation -
MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation
Semantic segmentation performs pixel-level classifica- tion to localize objects from different classes in the input image. Open-vocabulary semantic segmentation aims to... -
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Seg...
Weakly-supervised semantic segmentation using plain Vision Transformer (ViT) for Weakly-supervised Semantic Segmentation (WSSS). -
Channelized Axial Attention
Semantic segmentation is a fundamental task in many computer vision applications, which assigns a class label to each pixel in the image.
