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 1–50 of 58 papers

TitleStatusHype
IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion ModelsCode5
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual InversionCode5
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven GenerationCode5
Less-to-More Generalization: Unlocking More Controllability by In-Context GenerationCode5
StoryMaker: Towards Holistic Consistent Characters in Text-to-image GenerationCode4
MoMA: Multimodal LLM Adapter for Fast Personalized Image GenerationCode3
Generative Multimodal Models are In-Context LearnersCode3
Personalized Image Generation with Deep Generative Models: A Decade SurveyCode3
RectifID: Personalizing Rectified Flow with Anchored Classifier GuidanceCode2
DreamBench++: A Human-Aligned Benchmark for Personalized Image GenerationCode2
EZIGen: Enhancing zero-shot personalized image generation with precise subject encoding and decoupled guidanceCode2
FastComposer: Tuning-Free Multi-Subject Image Generation with Localized AttentionCode2
When StyleGAN Meets Stable Diffusion: a W+ Adapter for Personalized Image GenerationCode2
Gen4Gen: Generative Data Pipeline for Generative Multi-Concept CompositionCode2
Subject-Diffusion:Open Domain Personalized Text-to-Image Generation without Test-time Fine-tuningCode2
Resolving Multi-Condition Confusion for Finetuning-Free Personalized Image GenerationCode2
TextBoost: Towards One-Shot Personalization of Text-to-Image Models via Fine-tuning Text EncoderCode2
Personalized Text-to-Image Generation with Auto-Regressive ModelsCode1
Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image GenerationCode1
BootPIG: Bootstrapping Zero-shot Personalized Image Generation Capabilities in Pretrained Diffusion ModelsCode1
Conceptrol: Concept Control of Zero-shot Personalized Image GenerationCode1
PatchDPO: Patch-level DPO for Finetuning-free Personalized Image GenerationCode1
Personalized Image Generation with Large Multimodal ModelsCode1
PersonaMagic: Stage-Regulated High-Fidelity Face Customization with Tandem EquilibriumCode1
When StyleGAN Meets Stable Diffusion: a W_+ Adapter for Personalized Image GenerationCode1
HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectories—0
Identity Encoder for Personalized Diffusion—0
Imagine yourself: Tuning-Free Personalized Image Generation—0
InstantBooth: Personalized Text-to-Image Generation without Test-Time Finetuning—0
InstantFamily: Masked Attention for Zero-shot Multi-ID Image Generation—0
SerialGen: Personalized Image Generation by First Standardization Then Personalization—0
A Training-Free Style-Personalization via Scale-wise Autoregressive Model—0
FreeTuner: Any Subject in Any Style with Training-free Diffusion—0
Fast Personalized Text-to-Image Syntheses With Attention Injection—0
HiFi Tuner: High-Fidelity Subject-Driven Fine-Tuning for Diffusion Models—0
IDAdapter: Learning Mixed Features for Tuning-Free Personalization of Text-to-Image Models—0
Layout-and-Retouch: A Dual-stage Framework for Improving Diversity in Personalized Image Generation—0
LoRACLR: Contrastive Adaptation for Customization of Diffusion Models—0
MM-Diff: High-Fidelity Image Personalization via Multi-Modal Condition Integration—0
MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation—0
DreamCache: Finetuning-Free Lightweight Personalized Image Generation via Feature Caching—0
PersonaCraft: Personalized Full-Body Image Synthesis for Multiple Identities from Single References Using 3D-Model-Conditioned Diffusion—0
Personalize Anything for Free with Diffusion Transformer—0
DreamBlend: Advancing Personalized Fine-tuning of Text-to-Image Diffusion Models—0
ViPer: Visual Personalization of Generative Models via Individual Preference Learning—0
A4A: Adapter for Adapter Transfer via All-for-All Mapping for Cross-Architecture Models—0
AC-LoRA: Auto Component LoRA for Personalized Artistic Style Image Generation—0
PortraitBooth: A Versatile Portrait Model for Fast Identity-preserved Personalization—0
RAGAR: Retrieval Augment Personalized Image Generation Guided by Recommendation—0
DRC: Enhancing Personalized Image Generation via Disentangled Representation Composition—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