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20242026
most citedDiffFAE: Advancing High-fidelity One-shot Facial Appearance Editing with Space-sensitive Customization and Semantic Preservation

1 citations · 1 across the 6 of their papers we have counts for

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cs.CV2026

SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models

Zhengxuan Wei, Yi Dong, Zonghui Li +6

Low-Rank Adaptation (LoRA) merging can efficiently combine diverse generative capabilities from multiple trained LoRAs for a diffusion model. However, existing LoRA merging techniq…

cs.CV2025

Textualize Visual Prompt for Image Editing via Diffusion Bridge

Pengcheng Xu, Qingnan Fan, Fei Kou +5

Visual prompt, a pair of before-and-after edited images, can convey indescribable imagery transformations and prosper in image editing. However, current visual prompt methods rely…

cs.CV2024

RAP-SR: RestorAtion Prior Enhancement in Diffusion Models for Realistic Image Super-Resolution

Jiangang Wang, Qingnan Fan, Jinwei Chen +3

Benefiting from their powerful generative capabilities, pretrained diffusion models have garnered significant attention for real-world image super-resolution (Real-SR). Existing di…

cs.CV2024

CoMPaSS: Enhancing Spatial Understanding in Text-to-Image Diffusion Models

Gaoyang Zhang, Bingtao Fu, Qingnan Fan +5

Text-to-image (T2I) diffusion models excel at generating photorealistic images but often fail to render accurate spatial relationships. We identify two core issues underlying this…

cs.CV2024

LIPE: Learning Personalized Identity Prior for Non-rigid Image Editing

Aoyang Liu, Qingnan Fan, Shuai Qin +2

Although recent years have witnessed significant advancements in image editing thanks to the remarkable progress of text-to-image diffusion models, the problem of non-rigid image e…

cs.CV2024

FreeDiff: Progressive Frequency Truncation for Image Editing with Diffusion Models

Wei Wu, Qingnan Fan, Shuai Qin +3

Precise image editing with text-to-image models has attracted increasing interest due to their remarkable generative capabilities and user-friendly nature. However, such attempts f…