In skeleton-based action recognition, graph convolutional networks (GCN) have been applied to extract features based on the dynamic of the human body and the method has achieved excellent results recently. However, GC...
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Usually, image binarization plays a crucial role in automatic analysis of degraded documents from their captured images. However, this binarization task is often difficult due to a number of reasons including the high...
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Learning-based methods have attracted a lot of research attention and led to significant improvements in low-light image enhancement. However, most of them still suffer from two main problems: expensive computational ...
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Text-line segmentation is still considered challenging for complex background scene images. The success of text detection and recognition depends on the success of the text segmentation. This study presents a new meth...
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Script identification of text in natural scene images is challenging due to complex backgrounds, arbitrary orientations, different-sized characters, varying fonts, and multiple styles. Most existing methods are not ef...
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Estimating the degree of multiple personality traits in a single image is challenging due to the presence of multiple people, occlusion, poor quality etc. Unlike existing methods which focus on the classification of a...
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In the past few decades, due to rapid growth in industrialization, there has been a steady decline of the air quality along with an increase in the concentration of PM2.5. It is well known that a high PM2.5 concentrat...
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ISBN:
(数字)9798350359312
ISBN:
(纸本)9798350359329
In the past few decades, due to rapid growth in industrialization, there has been a steady decline of the air quality along with an increase in the concentration of PM2.5. It is well known that a high PM2.5 concentration adversely affects the environment and has hazardous impact on public health. Therefore, it is important to monitor the PM2.5 concentration at geographic locations where air quality monitoring stations are presently unavailable, especially in remote areas. Unfortunately, installation of such monitoring stations requires expensive instruments and constant maintenance. This paper presents a novel, low-cost and portable alternative to such measurement apparatus, where PM2.5 concentration is estimated based on image input obtained from a camera. The novelty of the present work lies in its hitherto unique attempt to capture information regarding PM2.5 content from visibility degradation caused by the pollutant which is further supplemented by important knowledge regarding seasonal and diurnal variation of it. The latter has a crucial role in the prevention of confounding effects arising from the presence of other weather and atmospheric elements. Another important highlight is the use of a full reference image metric as a feature, for which a powerful, dehazing algorithm has been employed. The results obtained are extremely promising, providing a close to accurate estimation of PM2.5 concentration with R
2
values far higher than reported in the literature. To summarize, the construction of a unique feature set, together with an appropriate machine learning algorithm, lead to an extremely reliable, stand-alone approach, deployable on a hand-held device such as a mobile and is a very significant contribution indeed of the proposed approach.
Reassembly tasks play a fundamental role in many fields and multiple approaches exist to solve specific reassembly problems. In this context, we posit that a general unified model can effectively address them all, irr...
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ISBN:
(数字)9798350353006
ISBN:
(纸本)9798350353013
Reassembly tasks play a fundamental role in many fields and multiple approaches exist to solve specific reassembly problems. In this context, we posit that a general unified model can effectively address them all, irrespective of the input data type (images, 3D, etc.). We introduce DiffAssemble, a Graph Neural Network (GNN)-based architecture that learns to solve reassembly tasks using a diffusion model formulation. Our method treats the elements of a set, whether pieces of 2D patch or 3D object fragments, as nodes of a spatial graph. Training is performed by introducing noise into the position and rotation of the elements and iteratively denoising them to reconstruct the coherent initial pose. DiffAssemble achieves state-of-the-art (SOTA) results in most 2D and 3D reassembly tasks and is the first learning-based approach that solves 2D puzzles for both rotation and translation. Furthermore, we highlight its remarkable reduction in run-time, performing 11 times faster than the quickest optimization-based method for puzzle solving. Code available at https://***/IIT-PAVIS/DiffAssemble.
Water causes degradation of quality in optical images captured underwater due to its physical properties of absorption and scattering. This degradation is further aggravated by the increase in water depth and the pres...
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ISBN:
(数字)9798350359312
ISBN:
(纸本)9798350359329
Water causes degradation of quality in optical images captured underwater due to its physical properties of absorption and scattering. This degradation is further aggravated by the increase in water depth and the presence of contaminated water. Transformers in the vision domain have made a quantum leap in many vision tasks such as detection, and segmentation but yet to make any progress in enhancing degraded underwater images. We propose a transformer-based model named “Aquaformer” which makes four major contributions: an adaptive layer normalization, replacement of masked cyclic shift with symmetric padding in window partitioning, a novel aggregation mechanism, and an adjustable fusion approach. These succeed in making the model a very powerful one, producing significantly better performance compared to the latest state-of-the-art methods. Testing on multiple benchmark datasets, employing both quantitative and qualitative metrics, establishes its supremacy.
In recent years, face recognition systems have faced increasingly security threats, making it essential to employ Face Anti-spoofing (FAS) to protect against various types of attacks in traditional scenarios like phon...
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