SOTAVerified

Personalized Image Generation

Utilizes single or multiple images that contain the same subject or style, along with text prompt, to generate images that contain that subject as well as match the textual description. Includes finetuning-based methods (e.g. DreamBooth, Textual Inversion) as well as encoder-based methods (e.g. E4T, ELITE, and IP-Adapter, etc.).

Papers

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Showing 31–40 of 58 papers

TitleStatusHype
Towards More Accurate Personalized Image Generation: Addressing Overfitting and Evaluation BiasCode0
A4A: Adapter for Adapter Transfer via All-for-All Mapping for Cross-Architecture Models—0
HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories—0
LoRACLR: Contrastive Adaptation for Customization of Diffusion Models—0
SerialGen: Personalized Image Generation by First Standardization Then Personalization—0
DreamBlend: Advancing Personalized Fine-tuning of Text-to-Image Diffusion Models—0
PersonaCraft: Personalized Full-Body Image Synthesis for Multiple Identities from Single References Using 3D-Model-Conditioned Diffusion—0
DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching—0
FaceChain-FACT: Face Adapter with Decoupled Training for Identity-preserved PersonalizationCode0
Imagine yourself: Tuning-Free Personalized Image Generation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DreamBooth LoRA SDXL v1.0Overall (CP * PF)0.52—Unverified
2IP-Adapter ViT-G SDXL v1.0Overall (CP * PF)0.38—Unverified
3Emu2 SDXL v1.0Overall (CP * PF)0.36—Unverified
4DreamBooth SD v1.5Overall (CP * PF)0.36—Unverified
5IP-Adapter-Plus ViT-H SDXL v1.0Overall (CP * PF)0.34—Unverified
6BLIP-Diffusion SD v1.5Overall (CP * PF)0.27—Unverified
7Textual Inversion SD v1.5Overall (CP * PF)0.24—Unverified