Image to Video Generation

Image-to-video generation aims to create realistic and temporally consistent video sequences from a single input image, often incorporating additional textual or other conditional inputs. Current research heavily utilizes diffusion models, often enhanced with modules for physics simulation, camera control, and motion awareness to improve realism and controllability. These advancements are improving video editing capabilities, enabling applications such as animation creation, interactive image manipulation, and enhancing online shopping experiences through dynamic fashion displays. The field is actively addressing challenges like maintaining visual consistency across frames and achieving precise control over generated motion.