1 citations · 1 across the 8 of their papers we have counts for
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UIP2P: Unsupervised Instruction-based Image Editing via Edit Reversibility Constraint
Enis Simsar, Alessio Tonioni, Yongqin Xian +2
We propose an unsupervised instruction-based image editing approach that removes the need for ground-truth edited images during training. Existing methods rely on supervised learni…
LoRACLR: Contrastive Adaptation for Customization of Diffusion Models
Enis Simsar, Thomas Hofmann, Federico Tombari +1
Recent advances in text-to-image customization have enabled high-fidelity, context-rich generation of personalized images, allowing specific concepts to appear in a variety of scen…
MegaPortrait: Revisiting Diffusion Control for High-fidelity Portrait Generation
Han Yang, Sotiris Anagnostidis, Enis Simsar +1
We propose MegaPortrait. It's an innovative system for creating personalized portrait images in computer vision. It has three modules: Identity Net, Shading Net, and Harmonization…
PixLens: A Novel Framework for Disentangled Evaluation in Diffusion-Based Image Editing with Object Detection + SAM
Stefan Stefanache, Lluís Pastor Pérez, Julen Costa Watanabe +3
Evaluating diffusion-based image-editing models is a crucial task in the field of Generative AI. Specifically, it is imperative to assess their capacity to execute diverse editing…