Augmented reality (AR) has proven to be an invaluable interactive medium to reduce
cognitive load by bridging the gap between the task-at-hand and relevant information by …

The reconstruction of 3D object from a single image is an important task in the field of
computer vision. In recent years, 3D reconstruction of single image using deep learning …

Multi-view stereo reconstruction (MVS) in the wild requires to first estimate the camera
intrinsic and extrinsic parameters. These are usually tedious and cumbersome to obtain yet …

We propose an end-to-end deep learning architecture that produces a 3D shape in
triangular mesh from a single color image. Limited by the nature of deep neural network …

3D reconstruction is a longstanding ill-posed problem, which has been explored for decades
by the computer vision, computer graphics, and machine learning communities. Since 2015 …

We present a novel learning approach to recover the 6D poses and sizes of unseen object
instances from an RGB-D image. To handle the intra-class shape variation, we propose a …

Reconstructing the 3D mesh of a general object from a single image is now possible thanks
to the latest advances of deep learning technologies. However, due to the nontrivial difficulty …

In this work, we aim to address the 3D scene stylization problem-generating stylized images
of the scene at arbitrary novel view angles. A straightforward solution is to combine existing …

Generating 3D point clouds is challenging yet highly desired. This work presents a novel
autoregressive model, PointGrow, which can generate diverse and realistic point cloud …

We propose Differentiable Surface Splatting (DSS), a high-fidelity differentiable renderer for
point clouds. Gradients for point locations and normals are carefully designed to handle …