Computer vision for autonomous vehicles: Problems, datasets and state of the art
Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …
State-of-the-art in 360 video/image processing: Perception, assessment and compression
Nowadays, 360° video/image has been increasingly popular and drawn great attention. The
spherical viewing range of 360° video/image accounts for huge data, which pose the …
spherical viewing range of 360° video/image accounts for huge data, which pose the …
Spherenet: Learning spherical representations for detection and classification in omnidirectional images
B Coors, AP Condurache… - Proceedings of the …, 2018 - openaccess.thecvf.com
Omnidirectional cameras offer great benefits over classical cameras wherever a wide field of
view is essential, such as in virtual reality applications or in autonomous robots …
view is essential, such as in virtual reality applications or in autonomous robots …
Learning representations from audio-visual spatial alignment
We introduce a novel self-supervised pretext task for learning representations from audio-
visual content. Prior work on audio-visual representation learning leverages …
visual content. Prior work on audio-visual representation learning leverages …
Learning spherical convolution for fast features from 360 imagery
While 360 cameras offer tremendous new possibilities in vision, graphics, and augmented
reality, the spherical images they produce make core feature extraction non-trivial …
reality, the spherical images they produce make core feature extraction non-trivial …
Pano-avqa: Grounded audio-visual question answering on 360deg videos
Abstract 360deg videos convey holistic views for the surroundings of a scene. It provides
audio-visual cues beyond predetermined normal field of views and displays distinctive …
audio-visual cues beyond predetermined normal field of views and displays distinctive …
Predicting head movement in panoramic video: A deep reinforcement learning approach
Panoramic video provides immersive and interactive experience by enabling humans to
control the field of view (FoV) through head movement (HM). Thus, HM plays a key role in …
control the field of view (FoV) through head movement (HM). Thus, HM plays a key role in …
Cube padding for weakly-supervised saliency prediction in 360 videos
Automatic saliency prediction in 360 videos is critical for viewpoint guidance applications
(eg, Facebook 360 Guide). We propose a spatial-temporal network which is (1) …
(eg, Facebook 360 Guide). We propose a spatial-temporal network which is (1) …
Coordinate Independent Convolutional Networks--Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds
Motivated by the vast success of deep convolutional networks, there is a great interest in
generalizing convolutions to non-Euclidean manifolds. A major complication in comparison …
generalizing convolutions to non-Euclidean manifolds. A major complication in comparison …
Kernel transformer networks for compact spherical convolution
Ideally, 360deg imagery could inherit the deep convolutional neural networks (CNNs)
already trained with great success on perspective projection images. However, existing …
already trained with great success on perspective projection images. However, existing …