UnifiedVisionGPT: Streamlining Vision-Oriented AI through Generalized
  Multimodal Framework
In the current landscape of artificial intelligence, foundation models serve
as the bedrock for advancements in both language and vision domains. OpenAI
GPT-4 has emerged as the pinnacle in large language models (LLMs), while the
computer vision (CV) domain boasts a plethora of state-of-the-art (SOTA) models
such as Meta's SAM and DINO, and YOLOS. However, the financial and
computational burdens of training new models from scratch remain a significant
barrier to progress. In response to this challenge, we introduce
UnifiedVisionGPT, a novel framework designed to consolidate and automate the
integration of SOTA vision models, thereby facilitating the development of
vision-oriented AI. UnifiedVisionGPT distinguishes itself through four key
features: (1) provides a versatile multimodal framework adaptable to a wide
range of applications, building upon the strengths of multimodal foundation
models; (2) seamlessly integrates various SOTA vision models to create a
comprehensive multimodal platform, capitalizing on the best components of each
model; (3) prioritizes vision-oriented AI, ensuring a more rapid progression in
the CV domain compared to the current trajectory of LLMs; and (4) introduces
automation in the selection of SOTA vision models, generating optimal results
based on diverse multimodal inputs such as text prompts and images. This paper
outlines the architecture and capabilities of UnifiedVisionGPT, demonstrating
its potential to revolutionize the field of computer vision through enhanced
efficiency, versatility, generalization, and performance. Our implementation,
along with the unified multimodal framework and comprehensive dataset, is made
publicly available at https://github.com/LHBuilder/SA-Segment-Anything.
655abcb93ff5ba1b1b3a644e
Chris Kelly
655abcb93ff5ba1b1b3a644f
Luhui Hu
655abcb93ff5ba1b1b3a6450
Cindy Yang
655abcb93ff5ba1b1b3a6451
Yu Tian
655abcb93ff5ba1b1b3a6452
Deshun Yang
655abcb93ff5ba1b1b3a6453
Bang Yang
admin_assigned
2023-11-20T13:52:13.303Z
63e32fbac123238b18a06d5e
/avatars/a6fab9c4430c7616ce050dab5b819f7e.svg
Bang Yang
user
yangbang18
655abcb93ff5ba1b1b3a6454
Zaoshan Huang
655abcb93ff5ba1b1b3a6455
Zihao Li
655abcb93ff5ba1b1b3a6456
Yuexian Zou
UnifiedVisionGPT: Streamlining Vision-Oriented AI through Generalized
  Multimodal Framework
In the current landscape of artificial intelligence, foundation models serve
as the bedrock for advancements in both language and vision domains. OpenAI
GPT-4 has emerged as the pinnacle in large language models (LLMs), while the
computer vision (CV) domain boasts a plethora of state-of-the-art (SOTA) models
such as Meta's SAM and DINO, and YOLOS. However, the financial and
computational burdens of training new models from scratch remain a significant
barrier to progress. In response to this challenge, we introduce
UnifiedVisionGPT, a novel framework designed to consolidate and automate the
integration of SOTA vision models, thereby facilitating the development of
vision-oriented AI. UnifiedVisionGPT distinguishes itself through four key
features: (1) provides a versatile multimodal framework adaptable to a wide
range of applications, building upon the strengths of multimodal foundation
models; (2) seamlessly integrates various SOTA vision models to create a
comprehensive multimodal platform, capitalizing on the best components of each
model; (3) prioritizes vision-oriented AI, ensuring a more rapid progression in
the CV domain compared to the current trajectory of LLMs; and (4) introduces
automation in the selection of SOTA vision models, generating optimal results
based on diverse multimodal inputs such as text prompts and images. This paper
outlines the architecture and capabilities of UnifiedVisionGPT, demonstrating
its potential to revolutionize the field of computer vision through enhanced
efficiency, versatility, generalization, and performance. Our implementation,
along with the unified multimodal framework and comprehensive dataset, is made
publicly available at https://github.com/LHBuilder/SA-Segment-Anything.
UnifiedVisionGPT is a novel framework that consolidates and automates the integration of state-of-the-art vision models, enhancing computer vision through efficiency, versatility, generalization, and performance.
foundation models large language models multimodal framework state-of-the-art vision models computer vision multimodal platform vision-oriented AI automation SOTA vision models SOTA