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Diffusion Personalization Tuning Free

This is a sub-class of diffusion personalization methods where the model is not required to be tuned on few user-specific images. Rather, the diffusion models are additionally trained on some dataset to allow forward pass personalization during test time.

Papers

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Showing 1–10 of 10 papers

TitleStatusHype
IP-Prompter: Training-Free Theme-Specific Image Generation via Dynamic Visual PromptingCode0
Arc2Face: A Foundation Model for ID-Consistent Human FacesCode4
Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMsCode5
InstantID: Zero-shot Identity-Preserving Generation in SecondsCode11
PhotoMaker: Customizing Realistic Human Photos via Stacked ID EmbeddingCode6
IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion ModelsCode5
Subject-Diffusion:Open Domain Personalized Text-to-Image Generation without Test-time Fine-tuningCode2
HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image ModelsCode1
FastComposer: Tuning-Free Multi-Subject Image Generation with Localized AttentionCode2
InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuning—0
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