Pose Adaptive Dual Mixup for Few-Shot Single-View 3D Reconstruction

Adaptive Contour Fitting for Pose-Invariant 3D Face Shape Reconstruction

Motivation Direct reconstruction of 3D face shape—solely based on a sparse set of 2D feature points localized by a facial landmark detector— offers an automatic, efficient and illumination-invariant alternative to the widely known analysis-by-synthesis framework, which is extremely timeconsuming considering the enormous parameter space for both shape and photometric properties. Given 2D landmar...

Coding-free Structured Light Means for Single-shot 3D Reconstruction

3D Model Reconstruction from Single View

In this paper the general problem of 3D surface reconstruction from single View image has been considered with prominence on combined source of information about the surface from image data. The aim is to construct a realistic, freeform wireframe 3D model of an object from a single view. We can easily construct the 3D model from multiple view and different known camera parameters but from the s...

Single-view-based 3D facial reconstruction method robust against pose variations

The 3D Morphable Model (3DMM) and the Structure from Motion (SfM) methods are widely used for 3D facial reconstruction from 2D single-view or multiple-view images. However, model-based methods suffer from disadvantages such as high computational costs and vulnerability to local minima and head pose variations. The SfM-based methods require multiple facial images in various poses. To overcome th...

Multi-View 3D Pose Estimation from Single Depth Images

In this paper, we investigate the problem of multi-view 3D human pose estimation from depth images using deep learning methods. We utilize an iterative approach that progressively makes changes to an initial mean pose by feeding back error predictions. Our model is evaluated on a newly collected dataset (ITOP) that contains 30K annotated depth images from top-down and frontal views. Experiments...