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…
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…
Tri-Prompting: Video Diffusion with Unified Control over Scene, Subject, and Motion
Zhenghong Zhou, Xiaohang Zhan, Zhiqin Chen +8
Recent video diffusion models have made remarkable strides in visual quality, yet precise, fine-grained control remains a key bottleneck that limits practical customizability for c…
How Long Can Unified Multimodal Models Generate Images Reliably? Taming Long-Horizon Interleaved Image Generation via Context Curation
Haoyu Chen, Qing Liu, Yuqian Zhou +7
Unified multimodal models hold the promise of generating extensive, interleaved narratives, weaving text and imagery into coherent long-form stories. However, current systems suffe…
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…