5 accepted papers
Advances in generative modeling have made it increasingly easy to fabricate realistic portrayals of individuals, creating serious risks for security, communication, and public trust. Detecting such person-driven manipulations requires systems that not only distinguish altered content from authentic
Existing models often struggle with complex temporal changes, particularly when generating videos with gradual attribute transitions.The most common prompt interpolation approach for motion transitions often fails to handle gradual attribute transitions, where inconsistencies tend to become more pro…
Sequential recommendation (SR) systems predict user preferences by analyzing time-ordered interaction sequences. A common challenge for SR is data sparsity, as users typically interact with only a limited number of items. While contrastive learning has been employed in previous approaches to addres…
Recent text-to-image (T2I) diffusion models have revolutionized image editing by empowering users to control outcomes using natural language. However the ease of image manipulation has raised ethical concerns with the potential for malicious use in generating deceptive or harmful content. To address…
Virtual try-on tasks have drawn increased attention. Prior arts focus on tackling this task via warping clothes and fusing the information at the pixel level with the help of semantic segmentation. However, conducting semantic segmentation is time-consuming and easily causes error accumulation over…