Synthesizing realistic facial expressions from

Description:To generate transitions between these facial expressions we use 3D shape morphing between the corresponding face models, while at the same time blending the corresponding textures. This is especially advantageous when training with small databases. Using our technique, we have been able to generate highly realistic face models and natural looking animations. In this paper, we propose the conditional difference adversarial autoencoder, CDAAE, for facial expression synthesis. This problem is challenging, in part due to a paucity of labeled facial expression data, making it difficult for algorithms to disambiguate changes due to identity and changes due to expression. Salesin in Identification of humans , Face recognition We present new techniques for creating photorealistic textured 3D facial models from photographs of a human subject, and for creating smooth transitions between different facial expressions by morphing between these different models. David Salesin Abstract We present new techniques for creating photorealistic textured 3D facial models from photographs of a human subject, and for creating smooth transitions between different facial expressions by morphing between these different models.

Views: 5530 Date: 2018-10-20 Favorited: 79