4 papers
Story-Iter: A Training-free Iterative Paradigm for Long Story Visualization
Jiawei Mao, Xiaoke Huang, Yunfei Xie +7
This paper introduces Story-Iter, a new training-free iterative paradigm to enhance long-story generation. Unlike existing methods that rely on fixed reference images to construct…
AllRestorer: All-in-One Transformer for Image Restoration under Composite Degradations
Jiawei Mao, Yu Yang, Xuesong Yin +2
Image restoration models often face the simultaneous interaction of multiple degradations in real-world scenarios. Existing approaches typically handle single or composite degradat…
Restorer: Removing Multi-Degradation with All-Axis Attention and Prompt Guidance
Jiawei Mao, Juncheng Wu, Yuyin Zhou +2
There are many excellent solutions in image restoration.However, most methods require on training separate models to restore images with different types of degradation.Although exi…
SwinStyleformer is a favorable choice for image inversion
Jiawei Mao, Guangyi Zhao, Xuesong Yin +1
This paper proposes the first pure Transformer structure inversion network called SwinStyleformer, which can compensate for the shortcomings of the CNNs inversion framework by hand…