Titlebook: Advances in Visual Computing; 17th International S George Bebis,Bo Li,Remco Chang Conference proceedings 2022 The Editor(s) (if applicable)

intoxicate

Photobombing Removal Benchmarkingndtruth. In our benchmark, several performance metrics are leveraged to compare the results of different methods with the groundtruth. The experiments provide insightful results which demonstrate the effectiveness of inpainting methods in this particular problem.

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Saliency Can Be All You Need in?Contrastive Self-supervised Learningive SSL algorithms subject to standard augmentation techniques. This evaluation, which was conducted across multiple datasets, indicated that the proposed technique indeed contributes to SSL. We hypothesize whether salient image segmentation may suffice as the only augmentation policy in Contrastive SSL when treating downstream segmentation tasks.

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過(guò)多

性上癮

Border Ownership, Category Selectivity and Beyondgiven edge of which side the object is that owns it. Here we present a method for determining border ownership using a deep neural network model. Additionally, the model learns selectivity for object categories, suggesting a potential relationship between border ownership information and object category-selectivity. ..

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偏狂癥

Sparse Kernel Transfer Learningng, a method that utilizes sparse coding and dictionary learning to pre-train the filters of a CNN. This pre-training is reminiscent of the unsupervised autoencoder training that used to be performed when stacking layers of a neural network. We argue that this dictionary transfer provides a better i

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Automatic Detection and?Recognition of?Products and?Planogram Conformity Analysis in?Real Time on?State in real time..The proposed method was validated with a dataset of 385 shelf images of 12 product categories from several stores of four different brands. Experimental results show that our approach is highly accurate in finding a product in all categories and for solving planogram conformity rat

悅耳

Debility

House Price Prediction via Visual Cues and Estate Attributesng the dataset collection, different features are extracted from the input data. Furthermore, a multi-kernel regression approach is used to predict the house price from both visual cues and estate attributes. The extensive experiments demonstrate the superiority of the proposed method over the basel