Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
원문 초록
We present a unified transformer, i.e., Show-o, that unifies multimodal understanding and generation. Unlike fully autoregressive models, Show-o unifies autoregressive and (discrete) diffusion modeling to adaptively handle inputs and outputs of various and mixed modalities. The unified model flexibly supports a wide range of vision-language tasks including visual question-answering, text-to-image generation, text-guided inpainting/extrapolation, and mixed-modality generation. Across various benchmarks, it demonstrates comparable or superior performance to existing individual models with an equivalent or larger number of parameters tailored for understanding or generation. This significantly highlights its potential as a next-generation foundation model. Code and models are released at https://github.com/showlab/Show-o.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Evaluating Attribute Confusion in Fashion Text-to-Image Generation
CharaConsist: Fine-Grained Consistent Character Generation
NeoBabel: A Multilingual Open Tower for Visual Generation
Ovis-U1 Technical Report
Rethink Sparse Signals for Pose-guided Text-to-image Generation
XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation
토론
이 논문과 연결된 포럼 글이 아직 없습니다.