5 papers
A Unified and Controllable Framework for Layered Image Generation with Visual Effects
Jinrui Yang, Qing Liu, Yijun Li +5
Recent image generation models produce impressive composites, but often fail to preserve the identity of user-provided content when editing specific elements: the surrounding scene…
Intra-Class Probabilistic Embeddings for Uncertainty Estimation in Vision-Language Models
Zhenxiang Lin, Maryam Haghighat, Will Browne +1
Vision-language models (VLMs), such as CLIP, have gained popularity for their strong open vocabulary classification performance, but they are prone to assigning high confidence sco…
UniSER: A Foundation Model for Unified Soft Effects Removal
Jingdong Zhang, Lingzhi Zhang, Qing Liu +12
Digital images are often degraded by soft effects such as lens flare, haze, shadows, and reflections, which reduce aesthetics even though the underlying pixels remain partially vis…
SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis
Hanrong Ye, Jason Kuen, Qing Liu +3
We propose SegGen, a highly-effective training data generation method for image segmentation, which pushes the performance limits of state-of-the-art segmentation models to a signi…
Perceptual Artifacts Localization for Image Synthesis Tasks
Lingzhi Zhang, Zhengjie Xu, Connelly Barnes +7
Recent advancements in deep generative models have facilitated the creation of photo-realistic images across various tasks. However, these generated images often exhibit perceptual…