GenWarp is a model designed for generating new viewpoint images from a single image. It employs a semantically-preserving generative deformation framework that allows text-to-image generation models to learn where deformation and generation should occur. This model addresses the limitations of existing methods by enhancing cross-view attention and self-attention, leveraging conditional generative models on the source view image, and incorporating geometric deformation signals to improve performance across different field scenarios.