Most scanning LiDAR sensors generate a sequence of point clouds in real-time. While
conventional 3D object detectors use a set of unordered LiDAR points acquired over a fixed …

Detecting objects in a video, known as Video Object Detection (VOD), is challenging since
appearance changes of objects over time may bring detection errors. Recent research has …

We present a video representation learning framework for real-time video object detection.
Our approach is based on the interesting observation that a powerful prior knowledge of …

This paper proposes a method exploiting temporal context with an attention mechanism for
detecting objects in real-time in a live streaming video. Video object detection is challenging …

This paper considers a model of object detection on aerial photographs and video using a
neural network in unmanned aerial systems. The development of artificial intelligence and …

Single-frame 3D detection is a well-studied vision problem with dedicated benchmarks and
a large body of work. This knowledge has translated to a myriad of real-world applications …

Deep-learning and large scale language-image training have produced image object
detectors that generalise well to diverse environments and semantic classes. However …

Moving object detection in low-luminance Images is one of the most fundamental and
difficult issues in machine vision. Therefore, in this paper, deep self-adaptive network (DSA …

Authors propose to use artificial neural networks (ANNs) for armaments identification based
on the analysis of digital images. They describe that this problem is caused by an increase …

Video is an essential resource because of its ability to hold space and time information.
Therefore, in the field of computer vision, a lot of research is conducted to extract various …