![]() The face region's initial point cloud was captured using the K-Mean Clustering algorithm. proposed reconstructing a dense 3D face point cloud from a single data frame captured from an RGB-D sensor. A variational segmentation model was proposed, which can represent a wide variety of glasses. proposed an automatic reconstruction of the human face and 3D epipolar geometry for eye-glass-based occlusion. The results from the original paper of Blanz and Vetter 1999, the first publicly available Morphable Model in 2009, and state-of-the-art facial re-enactment results and GAN-based models have been presented in the figure. įigure 7 shows the progressive improvement in 3DMM during the last twenty years. The model is constructed by registering the template mesh corresponding to the scanned face obtained from Iterative Closest Point (ICP) and Principal Component Analysis (PCA). Basel Face Model (BFM) is one of the publicly available 3DMM models. These models use low-dimensional representations for facial expressions, texture, and identity. Variants of 3DMM are available in the literature. This technique focuses on disentangling the facial colour and shape from the other factors, such as illumination, brightness, contrast, etc. The morphological faces ( morphs) are generated through dense correspondence. All the faces to be generated are in a dense point-to-point correspondence, which can be achieved through the face registration process. Section 8 holds the concluding remarks.įull size image 2.1 3D Morphable Model-based ReconstructionĪ 3D Morphable Model (3DMM) is a generative model for facial appearance and shape. Section 7 summarises current research challenges and future research directions. Section 6 discusses 3D face reconstruction's potential applications. Section 5 discusses the reconstruction process' tools and techniques. ![]() Section 3 discusses the performance evaluation measures followed by datasets used in reconstruction techniques in Sect. 4. The remainder of this paper is organised as follows: Sect. 2 covers variants of the 3D face reconstruction technique. The current and future challenges of 3D face reconstruction techniques have also been explored. The datasets, performance measures, and applicability of 3D face reconstruction are investigated. The hardware and software requirements of 3D face reconstruction techniques are presented. Various 3D face reconstruction techniques are discussed with pros and cons. The contribution of this paper is four-fold. This paper aims to study 3D face reconstruction using deep learning techniques and their applications in a real-life scenario. Most of the reconstruction research has preferred using GAN-based deep learning techniques. 1, in the last five years, 3d face research has grown with every passing year. The presented work's motivation lies in the detailed research surveys with deep learning of 3d point clouds and person re-identification. These are yet to be explored using deep learning techniques. ![]() Generative adversarial networks (GANs) are used for face swap and facial features modification in 2D faces. Recently, researchers have started working on mesh and voxel images. Most 3D face reconstruction techniques use 2D images during the reconstruction process. Register github account and push "Star" button.Face reconstruction involves completing the occluded face image. You can collect faceset of any celebrity that can be used in DeepFaceLab and share it in the community Sponsor deepfake research and DeepFaceLab development.īitcoin:bc1qkhh7h0gwwhxgg6h6gpllfgstkd645fefrd5s6z Something that was before DeepFaceLab and still remains in the past Swapping face using ONE single photo 一张图免训练换脸 ![]() Real-time face swap for PC streaming or video calls To achieve the highest quality, compose deepfake manually in video editors such as Davinci Resolve or Adobe AfterEffects Guide how to train the fake on Google Colab You can train fakes for free using Google Colab. A skill in programs such as AfterEffects or Davinci Resolve is also desirable. You should spend time studying the workflow and growing your skills. Unfortunately, there is no "make everything ok" button in DeepFaceLab. (also requires a skill in video editors such as Adobe After Effects or Davinci Resolve) More than 95% of deepfake videos are created with DeepFaceLab.ĭeepFaceLab is used by such popular youtube channels as deeptomcruise The leading software for creating deepfakes ![]()
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