Estimating depth from a single RGB image is an ill-posed and inherently ambiguous
problem. State-of-the-art deep learning methods can now estimate accurate 2D depth maps …

The field of single-view 3D shape reconstruction and generation using deep learning
techniques has seen rapid growth in the past five years. As the field is reaching a stage of …

We address the problem of efficiently estimating the rotation of a camera relative to the
canonical 3D Cartesian frame of an urban scene, under the so-called “Manhattan World” …

Our goal is to recover a complete 3D model from a depth image of an object. Existing
approaches rely on user interaction or apply to a limited class of objects, such as chairs. We …

Photo-editing software restricts the control of objects in a photograph to the 2D image plane.
We present a method that enables users to perform the full range of 3D manipulations …

3D morphable models are low-dimensional parameterizations of 3D object classes which
provide a powerful means of associating 3D geometry to 2D images. However, morphable …

This work investigates the use of particle swarm optimization (PSO) to recover the shape of a
surface from clouds of (either organized or scattered) noisy 3D data points, a challenging …

We present a monocular 3D reconstruction algorithm for inextensible deformable surfaces. It
uses point correspondences between a single image of the deformed surface taken by a …

Surface reconstruction is a very challenging problem arising in a wide variety of applications
such as CAD design, data visualization, virtual reality, medical imaging, computer animation …

Abstract top The problem addressed in this paper is the reconstruction of an object in the
form of a realistically textured 3D model from images taken with an uncalibrated camera. We …