6 papers · 1 filter
VibeFlow: Versatile Video Chroma-Lux Editing through Self-Supervised Learning
Yifan Li, Pei Cheng, Bin Fu +2
Video chroma-lux editing, which aims to modify illumination and color while preserving structural and temporal fidelity, remains a significant challenge. Existing methods typically…
Token Pruning for In-Context Generation in Diffusion Transformers
Junqing Lin, Xingyu Zheng, Pei Cheng +3
In-context generation significantly enhances Diffusion Transformers (DiTs) by enabling controllable image-to-image generation through reference examples. However, the resulting inp…
ReMix: Towards a Unified View of Consistent Character Generation and Editing
Benjia Zhou, Bin Fu, Pei Cheng +3
Recent advances in large-scale text-to-image diffusion models (e.g., FLUX.1) have greatly improved visual fidelity in consistent character generation and editing. However, existing…
LinguaLinker: Audio-Driven Portraits Animation with Implicit Facial Control Enhancement
Rui Zhang, Yixiao Fang, Zhengnan Lu +3
This study delves into the intricacies of synchronizing facial dynamics with multilingual audio inputs, focusing on the creation of visually compelling, time-synchronized animation…
EMMA: Your Text-to-Image Diffusion Model Can Secretly Accept Multi-Modal Prompts
Yucheng Han, Rui Wang, Chi Zhang +4
Recent advancements in image generation have enabled the creation of high-quality images from text conditions. However, when facing multi-modal conditions, such as text combined wi…
ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
Xiwei Hu, Rui Wang, Yixiao Fang +3
Diffusion models have demonstrated remarkable performance in the domain of text-to-image generation. However, most widely used models still employ CLIP as their text encoder, which…