Abstract Art Interpretation Using ControlNet
<|reference_start|>Abstract Art Interpretation Using ControlNet: Our study delves into the fusion of abstract art interpretation and text-to-image synthesis, addressing the challenge of achieving precise spatial control over image composition solely through textual prompts. Leveraging the capabilities of ControlNet, we empower users with finer control over the synthesis process, enabling enhanced manipulation of synthesized imagery. Inspired by the minimalist forms found in abstract artworks, we introduce a novel condition crafted from geometric primitives such as triangles.<|reference_end|>
@article{srivastava2024abstract,
    title={Abstract Art Interpretation Using ControlNet},
    author={Rishabh Srivastava, Addrish Roy},
    journal={arXiv preprint arXiv:2408.13287},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.13287},
    primaryClass={cs.CV cs.AI cs.LG}
}