Titlebook: Computer Vision – ECCV 2022; 17th European Confer Shai Avidan,Gabriel Brostow,Tal Hassner Conference proceedings 2022 The Editor(s) (if app

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Language Matters: A Weakly Supervised Vision-Language Pre-training Approach for Scene Text Detectioual features for learning effective scene text representations. With the learning of textual features, the pre-trained model can attend texts in images well with character awareness. Besides, these designs enable the learning from weakly annotated texts (i.e. partial texts in images without text bou

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,Toward Understanding WordArt: Corner-Guided Transformer for Scene Text Recognition,n a character contrastive loss to model the character-level feature, improving the feature representation for character classification. Thirdly, we utilize Transformer to learn the global feature on image-level and model the global relationship of the corner points, with the assistance of a corner-q

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珐琅

The Education of a Circus Clownfident predictions of the network to discriminate the intermediate feature embeddings in multiple stages. In the limited reconstruction case, our proposed approach, termed WS3D, has pioneer performance on the large-scale ScanNet on semantic segmentation and instance segmentation. Also, our proposed

Sigmoidoscopy

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Learning with Images in the Digital Ageructure and parallel token processing. Due to its extensive use of attention, it is robust on arbitrarily-oriented text, which is common in real-world images. Code, pretrained weights, and data are available at: ..

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