The history of text can be traced back over thousands of years. Rich and precise semantic
information carried by text is important in a wide range of vision-based application …

In this paper, we introduce InternVL 1.5, an open-source multimodal large language model
(MLLM) to bridge the capability gap between open-source and proprietary commercial …

We present DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-
world vision and language understanding applications. Our approach is structured around …

Context-aware STR methods typically use internal autoregressive (AR) language models
(LM). Inherent limitations of AR models motivated two-stage methods which employ an …

We present a high-performance method that can achieve mask-level instance segmentation
with only bounding-box annotations for training. While this setting has been studied in the …

End-to-end scene text spotting has attracted great attention in recent years due to the
success of excavating the intrinsic synergy of the scene text detection and recognition …

Large models have recently played a dominant role in natural language processing and
multimodal vision-language learning. However, their effectiveness in text-related visual …

In recent years, end-to-end scene text spotting approaches are evolving to the Transformer-
based framework. While previous studies have shown the crucial importance of the intrinsic …

End-to-end text-spotting, which aims to integrate detection and recognition in a unified
framework, has attracted increasing attention due to its simplicity of the two complimentary …

Time series data usually contains local and global patterns. Most of the existing feature
networks focus on local features rather than the relationships among them. The latter is also …