High-quality 3D reconstruction is an important topic in computer graphics and computer
vision with many applications, such as robotics and augmented reality. The advent of …

Partial convolution weights convolutions with binary masks and renormalizes on valid pixels.
It was originally proposed for image inpainting task because a corrupted image processed …

Over the past decade, we have witnessed an enormous amount of research effort dedicated
to the design of point cloud denoising techniques. In this article, we first provide a …

We present a real-time monocular 3D reconstruction system on a mobile phone, called
Mobile3DRecon. Using an embedded monocular camera, our system provides an online …

Learning with large-scale unlabeled data has become a powerful tool for pre-training Visual
Transformers (VTs). However, prior works tend to overlook that, in real-world scenarios, the …

Optical flow computation is essential in the early stages of the video processing pipeline.
This paper focuses on a less explored problem in this area, the 360∘ optical flow estimation …

In this article, we present GCN-Denoiser, a novel feature-preserving mesh denoising
method based on graph convolutional networks (GCNs). Unlike previous learning-based …

This paper proposes an image denoising training framework based on Wasserstein
Generative Adversarial Networks (WGAN) and applies it to cell image denoising. Cell image …

Self-supervised learning has proved to be a powerful approach to learn image
representations without the need of large labeled datasets. For underwater robotics, it is of …

Under-display imaging has recently received considerable attention in both academia and
industry. As a variation of this technique, under-display ToF (UD-ToF) cameras enable depth …