UniCSG adds staged semantic disentanglement and frequency-aware reconstruction to DiT diffusion models to improve content preservation and style fidelity in both text- and reference-guided generation.
In: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)
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UniCSG: Unified High-Fidelity Content-Constrained Style-Driven Generation via Staged Semantic and Frequency Disentanglement
UniCSG adds staged semantic disentanglement and frequency-aware reconstruction to DiT diffusion models to improve content preservation and style fidelity in both text- and reference-guided generation.