4 accepted papers
Text recognition in complex scenes is a challenging task in Computer Vision. In this paper, we propose an innovative framework for scene text recognition, ASANet, which features an Alternate Attention Enhancement Encoder and a Masked Dual-modal Decoder. The encoder incorporates a 12-layer Alternatin…
Vision Transformer, with the distinctive architecture and self-attention mechanisms, had profoundly influenced the field of computer vision, establishing Transformer-based models as benchmarks for semantic segmentation. In this study, we propose a pioneering hybrid model that fuses Kolmogorov-Arnold…
Oracle bone inscriptions, which are among the oldest known hieroglyphics in China, encompass rich historical and cultural information. However, the automatic recognition of oracle characters faces substantial challenges due to issues with data quality and long-tail distribution. This study introduce…
Lipreading refers to recognizing the speaker's speech content through the image sequence of lip movement without the speech signal. Currently, most models use a spatiotemporal (3D) convolutional layer combined with 2D CNN to extract spatial and temporal features from image sequences. However, compar…