Domain Image
Domain image research focuses on manipulating and understanding images across diverse contexts and domains, aiming to improve image generation, editing, and adaptation for various applications. Current research emphasizes developing robust models, often based on diffusion models, generative adversarial networks (GANs), and transformers, to address challenges like cross-domain translation, high-fidelity image editing, and copyright protection in AI-generated content. These advancements have significant implications for fields such as virtual try-on, medical image analysis, and content creation, enabling more efficient and realistic image manipulation and analysis techniques.
Papers
Learning Site-specific Styles for Multi-institutional Unsupervised Cross-modality Domain Adaptation
Han Liu, Yubo Fan, Zhoubing Xu, Benoit M. Dawant, Ipek Oguz
AnimateAnything: Fine-Grained Open Domain Image Animation with Motion Guidance
Zuozhuo Dai, Zhenghao Zhang, Yao Yao, Bingxue Qiu, Siyu Zhu, Long Qin, Weizhi Wang