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cs.CV2024
TLCM: Training-efficient Latent Consistency Model for Image Generation with 2-8 Steps
Qingsong Xie, Zhenyi Liao, Zhijie Deng +2
Distilling latent diffusion models (LDMs) into ones that are fast to sample from is attracting growing research interest. However, the majority of existing methods face two critica…
cs.CV2024
PEA-Diffusion: Parameter-Efficient Adapter with Knowledge Distillation in non-English Text-to-Image Generation
Jian Ma, Chen Chen, Qingsong Xie +1
Text-to-image diffusion models are well-known for their ability to generate realistic images based on textual prompts. However, the existing works have predominantly focused on Eng…
cs.CV2024
Subject-Diffusion:Open Domain Personalized Text-to-Image Generation without Test-time Fine-tuning
Jian Ma, Junhao Liang, Chen Chen +1
Recent progress in personalized image generation using diffusion models has been significant. However, development in the area of open-domain and non-fine-tuning personalized image…