8 papers
Twin Co-Adaptive Dialogue for Progressive Image Generation
Jianhui Wang, Yangfan He, Yan Zhong +12
Modern text-to-image generation systems have enabled the creation of remarkably realistic and high-quality visuals, yet they often falter when handling the inherent ambiguities in…
SCORE: Story Coherence and Retrieval Enhancement for AI Narratives
Qiang Yi, Yangfan He, Jianhui Wang +18
Large Language Models (LLMs) can generate creative and engaging narratives from user-specified input, but maintaining coherence and emotional depth throughout these AI-generated st…
Enhancing Intent Understanding for Ambiguous prompt: A Human-Machine Co-Adaption Strategy
Yangfan He, Jianhui Wang, Yijin Wang +18
Current image generation systems produce high-quality images but struggle with ambiguous user prompts, making interpretation of actual user intentions difficult. Many users must mo…
TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generation
Yuheng Feng, Jianhui Wang, Kun Li +5
Although text-to-image generation technologies have made significant advancements, they still face challenges when dealing with ambiguous prompts and aligning outputs with user int…
OMR-Diffusion:Optimizing Multi-Round Enhanced Training in Diffusion Models for Improved Intent Understanding
Kun Li, Jianhui Wang, Miao Zhang +1
Generative AI has significantly advanced text-driven image generation, but it still faces challenges in producing outputs that consistently align with evolving user preferences and…
Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion
Yangfan He, Sida Li, Jianhui Wang +11
Recent advancements in text-to-image (T2I) generation using diffusion models have enabled cost-effective video-editing applications by leveraging pre-trained models, eliminating th…