Personalized Image Generation
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Benchmarks
DreamBooth
Most implemented
DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models
Personalized Text-to-Image Generation with Auto-Regressive Models
Less-to-More Generalization: Unlocking More Controllability by In-Context Generation
Conceptrol: Concept Control of Zero-shot Personalized Image Generation
Papers
CopyCat: Improving Fine-Grained Subject Consistency in Subject-to-Image Models within Seconds
Recent subject-to-image models have achieved impressive progress in personalized image generation, yet they still struggle to preserve fine-grained subject-specific details. A major reason is the lack of high-quality fin…
Personalized Image GenerationPIPBench: A Profile-Inclusive Framework for Personalized Image Generation Evaluation
Recent text-to-image models such as DALLE-3 excel at following diverse prompts yet remain blind to individual aesthetic preferences. We study personalized image generation, where models must align outputs with a user's i…
Personalized Image GenerationMIBE: Multi-subject Interaction Benchmark and Evaluator for Personalized Image Generation
Multi-subject personalized image generation requires the precise rendering of all requested reference identities and their specified interactions based on a guiding prompt. However, state-of-the-art models still struggle…
Personalized Image GenerationScaling Multi-Reference Image Generation with Dynamic Reward Optimization
While personalized image generation has achieved remarkable progress, multi-reference image generation (MRIG) remains a challenging task. Most existing benchmarks fail to adequately evaluate complex MRIG scenarios, hinde…
Personalized Image GenerationImage EditingEPIG: Emotion-Based Prompting for Personalised Image Generation
Text-to-image diffusion models have achieved impressive results in synthesizing high-quality images from natural language prompts. However, commonly used prompting strategies remain relatively generic, limiting the model…
Personalized Image GenerationBypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization
With the growing concerns over copyright infringement in diffusion-based customization, adversarial attacks have emerged as a prominent defense strategy to prevent malicious content forgery in personalized image generati…
Personalized Image Generation