UniSpace: Unified Visual Representation and Scalable Multimodal Modeling
Semantic vision encoders have become a central visual interface for multimodal understanding and semantic conditioning in image generation. However, their final tokens discard fine-grained visual details, leading to poor pixel reconstruction and limiting their use in reconstruction-sensitive tasks such as image generation and editing. In this work, we ask whether understanding, generation, and editing can be modeled in a single visual representation space built from a pretrained semantic ViT. We show that the frozen Transformer blocks of a semantic ViT are not intrinsically unable to preserve visual details. Instead, the original patch parameterization drives the representation toward sem...
| Authors | Jinbo Yan, Limeng Qiao, Jie Qin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 9 August 2026 |
| Last updated at source | 9 August 2026 |
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