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Found 10 papers, 1 papers with code
SfmCAD: Unsupervised CAD Reconstruction by Learning Sketch-based Feature Modeling Operations
This paper introduces SfmCAD a novel unsupervised network that reconstructs 3D shapes by learning the Sketch-based Feature Modeling operations commonly used in modern CAD workflows.
Towards High-Fidelity Text-Guided 3D Face Generation and Manipulation Using only Images
In this paper, we propose a text-guided 3D faces generation method, refer as TG-3DFace, for generating realistic 3D faces using text guidance.
Reconstructing A Large Scale 3D Face Dataset for Deep 3D Face Identification
The experimental results show that the reconstructed 3D facial surfaces are useful and our 2D-aided deep 3D face identification framework is meaningful, facing the scarcity of 3D faces.
Learning Spectral Transform Network on 3D Surface for Non-rigid Shape Analysis
Designing a network on 3D surface for non-rigid shape analysis is a challenging task.
Discovering Influential Factors in Variational Autoencoder
In the field of machine learning, it is still a critical issue to identify and supervise the learned representation without manually intervening or intuition assistance to extract useful knowledge or serve for the downstream tasks.
Accurate Facial Parts Localization and Deep Learning for 3D Facial Expression Recognition
In particular, each textured 3D face scan is firstly represented as a 2D texture map and a depth map with one-to-one dense correspondence.
Neural Multi-Atlas Label Fusion: Application to Cardiac MR Images
There are two major challenges in this category of methods, i. e., atlas selection and label fusion.
ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI
Due to the combination of the advantages in model-based approach and deep learning approach, the ADMM-Nets achieve state-of-the-art reconstruction accuracies with fast computational speed.
Deep ADMM-Net for Compressive Sensing MRI
Compressive Sensing (CS) is an effective approach for fast Magnetic Resonance Imaging (MRI).
Deep Representation of Facial Geometric and Photometric Attributes for Automatic 3D Facial Expression Recognition
In this paper, we present a novel approach to automatic 3D Facial Expression Recognition (FER) based on deep representation of facial 3D geometric and 2D photometric attributes.
3D Facial Expression Recognition
Facial Expression Recognition
