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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.02765 |
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| _version_ | 1866915092139868160 |
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| author | Li, Yifan Lai, Zhixin Bao, Wentao Tan, Zhen Dao, Anh Sui, Kewei Shen, Jiayi Liu, Dong Liu, Huan Kong, Yu |
| author_facet | Li, Yifan Lai, Zhixin Bao, Wentao Tan, Zhen Dao, Anh Sui, Kewei Shen, Jiayi Liu, Dong Liu, Huan Kong, Yu |
| contents | Visual-language models (VLM) have emerged as a powerful tool for learning a unified embedding space for vision and language. Inspired by large language models, which have demonstrated strong reasoning and multi-task capabilities, visual large language models (VLLMs) are gaining increasing attention for building general-purpose VLMs. Despite the significant progress made in VLLMs, the related literature remains limited, particularly from a comprehensive application perspective, encompassing generalized and specialized applications across vision (image, video, depth), action, and language modalities. In this survey, we focus on the diverse applications of VLLMs, examining their using scenarios, identifying ethics consideration and challenges, and discussing future directions for their development. By synthesizing these contents, we aim to provide a comprehensive guide that will pave the way for future innovations and broader applications of VLLMs. The paper list repository is available: https://github.com/JackYFL/awesome-VLLMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_02765 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Visual Large Language Models for Generalized and Specialized Applications Li, Yifan Lai, Zhixin Bao, Wentao Tan, Zhen Dao, Anh Sui, Kewei Shen, Jiayi Liu, Dong Liu, Huan Kong, Yu Computer Vision and Pattern Recognition Artificial Intelligence Visual-language models (VLM) have emerged as a powerful tool for learning a unified embedding space for vision and language. Inspired by large language models, which have demonstrated strong reasoning and multi-task capabilities, visual large language models (VLLMs) are gaining increasing attention for building general-purpose VLMs. Despite the significant progress made in VLLMs, the related literature remains limited, particularly from a comprehensive application perspective, encompassing generalized and specialized applications across vision (image, video, depth), action, and language modalities. In this survey, we focus on the diverse applications of VLLMs, examining their using scenarios, identifying ethics consideration and challenges, and discussing future directions for their development. By synthesizing these contents, we aim to provide a comprehensive guide that will pave the way for future innovations and broader applications of VLLMs. The paper list repository is available: https://github.com/JackYFL/awesome-VLLMs. |
| title | Visual Large Language Models for Generalized and Specialized Applications |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2501.02765 |