4 accepted papers
Despite considerable efforts to enhance the generalization of 3D pose estimators without costly 3D annotations, existing data augmentation methods struggle in real-world scenarios with diverse human appearances and complex poses. We propose PoseSyn, a novel data synthesis framework that transforms a…
We present a new multi-modal face image generation method that converts a text prompt and a visual input such as a semantic mask or scribble map into a photo-realistic face image. To do this we combine the strengths of Generative Adversarial networks (GANs) and diffusion models (DMs) by employing th…
Text-driven localized editing of 3D objects is particularly difficult as locally mixing the original 3D object with the intended new object and style effects without distorting the object's form is not a straightforward process. To address this issue, we propose a novel NeRF-based model, Blending-Ne…
While 3D-based GAN techniques have been successfully applied to render photo-realistic 3D images with a variety of attributes while preserving view consistency, there has been little research on how to fine-control 3D images without limiting to a specific category of objects of their properties. To…