Computer Vision - ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XIX

The 39-volume set, consisting of the LNCS books 13661 to 13699, contains the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The papers cover various topics in computer vision, machine learning, deep neural networks, and more, with 1645 papers selected from 5804 submissions.

Format: Paperback / softback
Length: 761 pages
Publication date: 09 November 2022
Publisher: Springer International Publishing AG

The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision (ECCV) 2022, held in Tel Aviv, Israel, during October 23–27, 2022.

The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers cover a wide range of topics in computer vision, including:

Computer Vision: This field encompasses the development and application of algorithms for tasks such as image analysis, object detection, and scene understanding.

Machine Learning: Machine learning algorithms are used to analyze and interpret data, enabling computers to make predictions and decisions based on patterns.

Deep Neural Networks: Deep neural networks are a powerful tool for analyzing and processing complex data, particularly in areas such as image recognition and natural language processing.

Reinforcement Learning: Reinforcement learning involves training agents to make decisions in complex environments by receiving feedback in the form of rewards or penalties.

Object Recognition: Object recognition algorithms are used to identify and classify objects in images and videos.

Image Classification: Image classification algorithms are used to categorize images based on their content, such as objects, landscapes, or animals.

Image Processing: Image processing algorithms are used to enhance, modify, and analyze images, such as cropping, resizing, and color correction.

Object Detection: Object detection algorithms are used to identify and locate objects in images and videos.

Semantic Segmentation: Semantic segmentation algorithms are used to divide an image into different regions or objects based on their semantic meaning.

Human Pose Estimation: Human pose estimation algorithms are used to determine the position and orientation of human bodies in images and videos.

Three-Dimensional Reconstruction: Three-dimensional reconstruction algorithms are used to create 3D models of objects and scenes from 2D images.

Stereo Vision: Stereo vision algorithms are used to create depth perception and 3D reconstructions from multiple camera images.

Computational Photography: Computational photography algorithms are used to enhance and manipulate images captured by cameras.

Neural Networks: Neural networks are a type of artificial intelligence algorithm that mimics the behavior of the human brain.

Image Coding: Image coding algorithms are used to compress and encode images for storage and transmission.

Image Reconstruction: Image reconstruction algorithms are used to recreate images from degraded or incomplete data.

Object Recognition: Object recognition algorithms are used to identify and classify objects in images and videos.

Motion Estimation: Motion estimation algorithms are used to estimate the motion of objects in images and videos.

These proceedings represent the latest advancements in computer vision research and provide a valuable resource for researchers, practitioners, and students in the field.

Weight: 1234g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031197994
Edition number: 1st ed. 2022