4 papers
Conflict-Aware Additive Guidance for Flow Models under Compositional Rewards
Xuehui Yu, Fucheng Cai, Meiyi Wang +2
Inference-time guided sampling steers state-of-the-art diffusion and flow models without fine-tuning by interpreting the generation process as a controllable trajectory. This provi…
Towards Any-Quality Image Segmentation via Generative and Adaptive Latent Space Enhancement
Guangqian Guo, Aixi Ren, Yong Guo +6
Segment Anything Models (SAMs), known for their exceptional zero-shot segmentation performance, have garnered significant attention in the research community. Nevertheless, their p…
Segment Any-Quality Images with Generative Latent Space Enhancement
Guangqian Guo, Yong Guo, Xuehui Yu +3
Despite their success, Segment Anything Models (SAMs) experience significant performance drops on severely degraded, low-quality images, limiting their effectiveness in real-world…
ReLayout: Integrating Relation Reasoning for Content-aware Layout Generation with Multi-modal Large Language Models
Jiaxu Tian, Xuehui Yu, Yaoxing Wang +3
Content-aware layout aims to arrange design elements appropriately on a given canvas to convey information effectively. Recently, the trend for this task has been to leverage large…