4 citations · 7 across the 5 of their papers we have counts for
5 papers
SeFi-Image: A Text-to-Image Foundation Model with Semantic-First Diffusion
Ruoyu Feng, Jinming Liu, Yuqi Wang +7
Training image generation foundation models consumes substantial resources. Previous methods have attempted to leverage semantic guidance to accelerate the training process, yet th…
Federated Learning via Input-Output Collaborative Distillation
Xuan Gong, Shanglin Li, Yuxiang Bao +6
Federated learning (FL) is a machine learning paradigm in which distributed local nodes collaboratively train a central model without sharing individually held private data. Existi…
ZONE: Zero-Shot Instruction-Guided Local Editing
Shanglin Li, Bohan Zeng, Yutang Feng +8
Recent advances in vision-language models like Stable Diffusion have shown remarkable power in creative image synthesis and editing.However, most existing text-to-image editing met…
IPDreamer: Appearance-Controllable 3D Object Generation with Complex Image Prompts
Bohan Zeng, Shanglin Li, Yutang Feng +9
Recent advances in 3D generation have been remarkable, with methods such as DreamFusion leveraging large-scale text-to-image diffusion-based models to guide 3D object generation. T…
Controllable Mind Visual Diffusion Model
Bohan Zeng, Shanglin Li, Xuhui Liu +6
Brain signal visualization has emerged as an active research area, serving as a critical interface between the human visual system and computer vision models. Although diffusion mo…