Computer Vision
We propose a real world data set comprising light field images of 19 objects captured with the Lytro Illum camera in outdoor scenes and their corresponding 3D point clouds, as ground truth, captured with the 3dMD scanner. This data set allows more precise 3D pointcloud level comparison of algorithms for the task of depth estimation or 3D point cloud reconstruction from light field images.
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303 Views
130 videos are available, captured in Patras, Greece, displaying drivers in real cars, moving under nighttime conditions where drowsiness detection is more important.The participating drivers are: 11 males and 10 females with different features (hair color, beard, glasses, etc). The videos are split in 2 categories:
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1970 Views
Early detection of retinal diseases is one of the most important means of preventing partial or permanent blindness in patients. One of the major stumbling blocks for manual retinal examination is the lack of a sufficient number of qualified medical personnel per capita to diagnose diseases.
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5878 Views
Semi-supervised video object segmentation aims to leverage the ground truth object masks given for the first frame to segment video sequences at the pixel level. OVOS is a dataset to evaluate the performance of video object segmentation under occlusions.
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500 Views
This article is a dataset of portrait Thangka images. We have annotated the four categories of Thangka images at the pixel level, namely figures, headlights, backlights and pedestals. Experiments on the dataset can help scholars strengthen their understanding of Thangka images. research on image content
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158 Views
This dataset includes the images, and instance segmentation masks to evaluate panoptic segmentation in the food domain.
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506 Views
Please cite the following paper when using this dataset:
N. Thakur and C.Y. Han, “An Exploratory Study of Tweets about the SARS-CoV-2 Omicron Variant: Insights from Sentiment Analysis, Language Interpretation, Source Tracking, Type Classification, and Embedded URL Detection,” Journal of COVID, 2022, Volume 5, Issue 3, pp. 1026-1049
Abstract
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1694 Views
Accurate fire load (combustible objects) information is crucial for safety design and resilience assessment of buildings. Traditional fire load acquisition methods, such as fire load survey, which are time-consuming, tedious, and error-prone, failed to adapt to dynamic changed indoor scenes. As a starting point of automatic fire load estimation, fast recognition and detection of indoor fire load are important. Thus, A dataset containing images of indoor scenes and annotations of instance segmentation is developed in this research.
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1619 Views
The C3I Synthetic Face Depth Dataset consists of 3D virtual human models and 2D rendered RGB and GT depth images in zipped version into two folders for male and female.
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1743 Views