Camera matrix and dense/sparse landmarks prediction via a single network. Lightweight render library, 5x faster (3ms vs 15ms) than the Sim3DR tools. CPU real-time face deteciton, alignment, and reconstruction pipeline. Reimplementation of (ECCV 2020) Towards Fast, Accurate and Stable 3D Dense Face Alignment via Tensorflow Lite framework, face mesh, head pose, landmarks, and more. For such tasks, commonly used multi-linear morphable models, which provide semantic control over facial identity and expression, often lack quality and expressivity due to their. To further enhance the quality of reconstructed images, we explore both pixel difference and perceptual loss for training the NbNets.įace models built from 3D face databases are often used in computer vision and graphics tasks such as face reconstruction, replacement, tracking and manipulation. MAI et al.: ON THE RECONSTRUCTION OF FACE IMAGES FROM DEEP FACE TEMPLATES 3 we trained a face image generator, DCGAN, to augment available public domain face datasets.in which case a substantial amount of preprocessing might be necessary. 3D reconstruction from video/images is now a mature and extremely useful technology, though it can be challenging to obtain good results where the object/terrain is large, illumination cannot be controlled, under vibration, where multiple videos exist of an object of interest, with partial or temporary occlusions, etc.Liu proposed a joint face alignment and 3D face. For instance, Tran and Liu proposed an innovative network to learn a nonlinear 3DMM model from a large set of in-the-wild face images. Mugshot-based face reconstruction Single-view face reconstruction has attracted lots of attentions and made a great progress.
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