Titlebook: Computer Vision – ACCV 2022; 16th Asian Conferenc Lei Wang,Juergen Gall,Rama Chellappa Conference proceedings 2023 The Editor(s) (if applic

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书目名称Computer Vision – ACCV 2022影响因子(影响力)




书目名称Computer Vision – ACCV 2022影响因子(影响力)学科排名




书目名称Computer Vision – ACCV 2022网络公开度




书目名称Computer Vision – ACCV 2022网络公开度学科排名




书目名称Computer Vision – ACCV 2022被引频次




书目名称Computer Vision – ACCV 2022被引频次学科排名




书目名称Computer Vision – ACCV 2022年度引用




书目名称Computer Vision – ACCV 2022年度引用学科排名




书目名称Computer Vision – ACCV 2022读者反馈




书目名称Computer Vision – ACCV 2022读者反馈学科排名

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Introduction: Mainstreaming the Marginal,r a predicted value might provide great information beyond the prediction itself. To address this goal, using a probabilistic loss was proven efficient for aleatoric uncertainty, which aims at capturing noise originating from the observations. For multidimensional predictions, this estimated noise i

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Sony Jalarajan Raj,Adith K. Suresheven an appropriate evaluation metric is still missing. Indeed, existing metrics only focus on the writing orders but overlook the fidelity of glyphs. Taking both facets into account, we come up with two new metrics, the adaptive intersection on union (AIoU) which eliminates the influence of various

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Deepali Yadav,Vipin K. Kadavatherally deliver incomplete CD regions and irregular CD boundaries due to the limited representation ability of the extracted visual features. To relieve these issues, in this work we propose a novel learning framework named Fully Transformer Network (FTN) for remote sensing image CD, which improves t

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Emergence of the Second Digital Wave,d at image-level or pixel-level. Considering that pixel-level anomaly classification achieves better representation learning in a finer-grained manner, we regard data augmentation transforms as a self-supervised segmentation task from which to extract the critical and representative information from

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Felicitous

The Digital Synaptic Neural Substrateogy of lane lines in complex scenarios; moreover, different types and instances of lane lines need to be distinguished. Most existing studies are based only on a single-level feature map extracted by deep neural networks. However, both high-level and low-level features are important for lane detecti

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The Impetus for Digital Televisionintensities. Due to the similar visual appearance of TCs in adjacent intensities, the discriminative image representation plays an important role in TC intensity estimation. Existing works mainly revolve around the continuity of intensity which may result in a crowded feature distribution and perfor