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

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: 741 pages
Publication date: 12 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, enabling applications such as autonomous vehicles and facial recognition systems.

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

Image Processing: Image processing algorithms are used to enhance, modify, and analyze images, enabling tasks such as image restoration and image compression.

Object Detection: Object detection algorithms are used to identify and locate objects in images and videos, enabling applications such as security systems and autonomous vehicles.

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

Human Pose Estimation: Human pose estimation algorithms are used to estimate the pose of a human body in images and videos, enabling applications such as virtual reality and human-computer interaction.

Three-Dimensional Reconstruction: Three-dimensional reconstruction algorithms are used to create three-dimensional models of objects and scenes from two-dimensional images and videos.

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 and videos using computer vision techniques.

Neural Networks: Neural networks are a class of algorithms that are inspired by the structure and function of the human brain. They are used for a wide range of tasks, including image recognition, natural language processing, and machine learning.

Image Coding: Image coding algorithms are used to reduce the size of images while maintaining their quality, enabling efficient storage and transmission of images over networks.

Image Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data, enabling tasks such as medical imaging and satellite imaging.

Object Recognition: Object recognition algorithms are used to identify and classify objects in images and videos, enabling applications such as autonomous vehicles and facial recognition systems.

Motion Estimation: Motion estimation algorithms are used to estimate the motion of objects in images and videos, enabling applications such as video surveillance and sports analysis.

These proceedings represent the latest advancements in computer vision research and technology, and they will be valuable to researchers, practitioners, and students in the field.

The 17th European Conference on Computer Vision (ECCV) 2022, held in Tel Aviv, Israel, from October 23-27, 2022, witnessed the presentation of a remarkable 1645 papers. These papers, meticulously reviewed and selected from a staggering 5804 submissions, cover a diverse range of topics within the field of computer vision.

Computer vision, a multidisciplinary domain, encompasses a wide array of techniques and algorithms aimed at understanding and interpreting visual data. The papers presented at ECCV 2022 delve into various aspects of computer vision, including:

Computer Vision: This overarching field encompasses the development and application of algorithms for tasks such as image analysis, object detection, and scene understanding. Researchers explore innovative methods to enhance the accuracy, efficiency, and robustness of computer vision systems, enabling them to perform tasks in diverse environments and applications.

Machine Learning: Machine learning algorithms play a pivotal role in computer vision. These algorithms are trained on large datasets to learn patterns and make predictions based on the data. They are widely used in various applications, including image recognition, object detection, and facial recognition.

Deep Neural Networks: Deep neural networks, a subset of machine learning, are characterized by their ability to learn complex patterns and make predictions with high accuracy. They are extensively used in image recognition, object detection, and facial recognition tasks.

Reinforcement Learning: Reinforcement learning involves training agents to make decisions in complex environments by receiving feedback in the form of rewards or penalties. This approach is particularly useful in autonomous vehicles, robotics, and game playing.

Object Recognition: Object recognition algorithms are employed to identify and classify objects in images and videos. These algorithms are crucial in various applications, such as autonomous vehicles, surveillance systems, and medical imaging.

Image Classification: Image classification algorithms categorize images based on their content, such as flowers, animals, or buildings. These algorithms are widely used in image retrieval, content-based indexing, and image analysis.

Image Processing: Image processing algorithms are used to enhance, modify, and analyze images. These algorithms are employed in various applications, including image restoration, image compression, and image segmentation.

Object Detection: Object detection algorithms are employed to identify and locate objects in images and videos. These algorithms are crucial in various applications, such as security systems, autonomous vehicles, and medical imaging.

Semantic Segmentation: Semantic segmentation algorithms are used to divide an image into different regions based on their semantic meaning, such as objects, backgrounds, or faces. These algorithms are widely used in medical imaging, autonomous vehicles, and scene understanding.

Human Pose Estimation: Human pose estimation algorithms are employed to estimate the pose of a human body in images and videos. These algorithms are crucial in various applications, such as virtual reality, human-computer interaction, and sports analysis.

Three-Dimensional Reconstruction: Three-dimensional reconstruction algorithms are used to create three-dimensional models of objects and scenes from two-dimensional images and videos. These algorithms are widely used in computer graphics, archaeology, and virtual reality.

Stereo Vision: Stereo vision algorithms are used to create depth perception and 3D reconstructions from multiple camera images. These algorithms are widely used in autonomous vehicles, robotics, and augmented reality.

Computational Photography: Computational photography algorithms are used to enhance and manipulate images and videos using computer vision techniques. These algorithms are widely used in photography, video editing, and content creation.

Neural Networks: Neural networks are a class of algorithms inspired by the structure and function of the human brain. They are widely used in various applications, including image recognition, natural language processing, and machine learning.

Image Coding: Image coding algorithms are used to reduce the size of images while maintaining their quality. These algorithms are crucial in various applications, such as image transmission, storage, and retrieval.

Image Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data. These algorithms are widely used in medical imaging, satellite imaging, and remote sensing.

Object Recognition: Object recognition algorithms are used to identify and classify objects in images and videos. These algorithms are crucial in various applications, such as autonomous vehicles, surveillance systems, and facial recognition.

Motion Estimation: Motion estimation algorithms are used to estimate the motion of objects in images and videos. These algorithms are widely used in video surveillance, sports analysis, and robotics.

The 17th European Conference on Computer Vision (ECCV) 2022 serves as a platform for researchers, practitioners, and students to exchange ideas, share their findings, and collaborate on advancing the state-of-the-art in computer vision. The high-quality papers presented at the conference highlight the significant contributions made by the global computer vision community, and they will undoubtedly have a profound impact on the future of this field.

In conclusion, 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, covering a wide range of topics in computer vision. The papers cover a diverse range of topics, including computer vision, machine learning, deep neural networks, reinforcement learning, object recognition, image classification, image processing, object detection, semantic segmentation, human pose estimation, 3d reconstruction, stereo vision, computational photography, neural networks, image coding, image reconstruction, object recognition, motion estimation, and more. The proceedings represent the latest advancements in computer vision research and technology, and they will be valuable to researchers, practitioners, and students in the field.

Weight: 1205g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031198236
Edition number: 1st ed. 2022