Photometric stereo recovers the surface normals of an object from multiple images with
varying shading cues, ie, modeling the relationship between surface orientation and …

Enhancing underwater images captured under mixed artificial and natural lighting
conditions presents two critical challenges. Existing methods lack a unified luminance …

In this paper, we propose a novel method, namely GR-PSN, which learns surface normals
from photometric stereo images and generates the photometric images under distant …

In the realm of precision medicine, the potential of deep learning is progressively harnessed
to facilitate intricate clinical decision-making, especially when navigating multifaceted …

Compound facial expressions involve combinations of basic emotions, posing challenges to
automatic facial expression recognition research. The focus of existing studies in facial …

With the introduction of deep learning, a significant amount of research has been conducted
in the field of computer vision in the past decade. In particular, research on object detection …

Abstract Visual Simultaneous Localization and Mapping (VSLAM) is a critical foundation in
mobile robotics and augmented reality (AR). However, VSLAM faces challenges in dynamic …

Object detection plays a crucial role in scene understanding and has extensive practical
applications. In the field of remote sensing object detection, both detection accuracy and …

In this study, we propose a meticulous method for the three-dimensional modeling of slope
models using structured light, a swift and cost-effective technique. Our approach aims to …

Deep learning is an important research topic in the field of image super-resolution.
Problematically, the performance of existing hyperspectral image super-resolution networks …