The increasingly common use of incidental satellite images for stereo reconstruction versus
rigidly tasked binocular or trinocular coincident collection is helping to enable timely global …

Visual perception plays an important role in autonomous driving. One of the primary tasks is
object detection and identification. Since the vision sensor is rich in color and texture …

The effective implementation of machine vision has played a crucial role in advancing
intelligent aquaculture across various domains. Stereo vision, as a branch of machine …

Scene understanding is paramount in robotics, self-navigation, augmented reality, and many
other fields. To fully accomplish this task, an autonomous agent has to infer the 3D structure …

Stereo matching is a fundamental technique for many vision and robotics applications. State-
of-the-art methods either employ convolutional neural networks with spatially-shared kernels …

Estimating the motion of the camera together with the 3D structure of the scene from a
monocular vision system is a complex task that often relies on the so-called scene rigidity …

Semantic segmentation and stereo matching are two essential components of 3D
environmental perception systems for autonomous driving. Nevertheless, conventional …

We present a self-supervised learning framework to estimate the individual object motion
and monocular depth from video. We model the object motion as a 6 degree-of-freedom …

Although instance-aware perception is a key prerequisite for many autonomous robotic
applications, most of the methods only partially solve the problem by focusing solely on …

Bio-inspired event cameras have been considered effective alternatives to traditional frame-
based cameras for stereo depth estimation, especially in challenging conditions such as low …