34 citations · 56 across the 23 of their papers we have counts for
6 papers · 1 filter
Improving Image Restoration through Removing Degradations in Textual Representations
Jingbo Lin, Zhilu Zhang, Yuxiang Wei +3
In this paper, we introduce a new perspective for improving image restoration by removing degradation in the textual representations of a given degraded image. Intuitively, restora…
Black-Box Tuning of Vision-Language Models with Effective Gradient Approximation
Zixian Guo, Yuxiang Wei, Ming Liu +4
Parameter-efficient fine-tuning (PEFT) methods have provided an effective way for adapting large vision-language models to specific tasks or scenarios. Typically, they learn a very…
Decoupled Textual Embeddings for Customized Image Generation
Yufei Cai, Yuxiang Wei, Zhilong Ji +3
Customized text-to-image generation, which aims to learn user-specified concepts with a few images, has drawn significant attention recently. However, existing methods usually suff…
Inferring and Leveraging Parts from Object Shape for Improving Semantic Image Synthesis
Yuxiang Wei, Zhilong Ji, Xiaohe Wu +3
Despite the progress in semantic image synthesis, it remains a challenging problem to generate photo-realistic parts from input semantic map. Integrating part segmentation map can…
ControlVideo: Training-free Controllable Text-to-Video Generation
Yabo Zhang, Yuxiang Wei, Dongsheng Jiang +3
Text-driven diffusion models have unlocked unprecedented abilities in image generation, whereas their video counterpart still lags behind due to the excessive training cost of temp…
ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation
Yuxiang Wei, Yabo Zhang, Zhilong Ji +3
In addition to the unprecedented ability in imaginary creation, large text-to-image models are expected to take customized concepts in image generation. Existing works generally le…