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Abstract
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This dataset is utilized for adversarial camouflage generation. We collect vehicle datasets in the CARLA simulation environment under 16 weather conditions. These weather conditions are generated by combining four sun altitude angles (-90°, 10°, 45°, 90°) with four fog densities (0, 25, 50, 90). Within each weather scenario, we randomly choose 16 locations for texture generation. Camera transformation values are randomly selected within specified intervals at each car location.
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400 Views
Smart focal-plane and in-chip image processing has emerged as a crucial technology for vision-enabled embedded systems with energy efficiency and privacy. However, the lack of special datasets providing examples of the data that these neuromorphic sensors compute to convey visual information has hindered the adoption of these promising technologies.
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The database presented consists of a set of images of the human hand making signs (20) at various angles, corresponding to the Colombian alphabet of signs established by the National Institute for the Deaf (INSOR). These signs are characterized by being static, that is, they do not require movement to be performed.
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206 Views
The database presented consists of a set of images of the human hand making signs (20) at various angles, corresponding to the Colombian alphabet of signs established by the National Institute for the Deaf (INSOR). These signs are characterized by being static, that is, they do not require movement to be performed.
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153 Views
As an artificial structure, tailings ponds exhibit regular geometric shapes and relatively straight dams in HRRSIs. Because the typical tailings dam is composed of an initial dam and successive accumulation dams, the tailings dam structure presents obvious linear stripe characteristics. The initial dam, constructed using sand, gravel, or concrete, has a bright color, while the color of the accumulation dam varies based on factors such as particle size, soil coverage, and vegetation restoration.
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Egocentric video and Inertial sensor data Kitchen activity dataset is the first V-S-S interaction-focused dataset for the ego-HAR task.
It consists of sequences of everyday kitchen activities involving rich interactions among the subject's body, object, and environment.
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The dataset is obtained through the transformation of mathematical tools and image processing techniques based on TTPLA. The original TTPLA dataset consisted of aerial wire data captured through pinhole cameras. After our conversion, we obtained the corresponding fisheye aerial wire data. It includes both the original images and annotated images, significantly reducing the annotation workload for fisheye wire data. We now make it publicly available for researchers to study and learn from.
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A novel image deblurring dataset for materials science and light-optical microscopy. This dataset provides images with real out-of-focus and motion blur and a sharp reference image for each observation. The dataset includes image samples of lithium-ion batteries, Fe-Nd-B sintered magnets, 100Cr6 steel with a partially bainitic microstructure, and aluminium-silicon casting alloys. The dataset was acquired using a ZEISS AxioImager.Z2 Vario light microscope and the 6-megapixel camera Axiocam 506 color.
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157 Views
In practical media distribution systems, visual content usually undergoes multiple stages of quality degradation along the delivery chain, but the pristine source content is rarely available at most quality monitoring points along the chain to serve as a reference for quality assessment. As a result, full-reference (FR) and reduced-reference (RR) image quality assessment (IQA) methods are generally infeasible. Although no-reference (NR) methods are readily applicable, their performance is often not reliable.
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310 Views