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

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: 743 pages
Publication date: 13 November 2022
Publisher: Springer International Publishing AG

The 39-volume set, comprising the LNCS books 13661 until 13699, represents the refereed proceedings of the 17th European Conference on Computer Vision (ECCV 2022), held in Tel Aviv, Israel, from October 23 to 27, 2022. A total of 1645 papers were presented in these proceedings, following a rigorous review process from a pool of 5804 submissions. These papers cover a wide range of topics within the field of computer vision, including:

Computer Vision: This encompasses the study and development of algorithms and systems for understanding and interpreting visual data, such as images, videos, and 3D scenes. It involves techniques such as image processing, pattern recognition, object detection, and scene analysis.

Machine Learning: Machine learning is a branch of computer science that focuses on teaching computers to learn from data, without being explicitly programmed. It involves techniques such as supervised learning, unsupervised learning, and reinforcement learning, which allow computers to analyze and predict patterns in data.

Deep Neural Networks: Deep neural networks are a type of neural network architecture that uses multiple layers of interconnected neurons to model and analyze complex data. They have been widely used in areas such as image recognition, speech recognition, and natural language processing.

Reinforcement Learning: Reinforcement learning is a type of machine learning that involves learning by interacting with an environment. It involves agents that make decisions in an environment and receive rewards or penalties based on their actions. Reinforcement learning is used in areas such as autonomous vehicles, game playing, and robotics.

Object Recognition: Object recognition is the process of identifying and categorizing objects in images or videos. It involves techniques such as feature extraction, classification, and tracking. Object recognition is used in areas such as security, surveillance, and autonomous systems.

Image Classification: Image classification is the process of assigning a label to an image based on its content. It involves techniques such as convolutional neural networks, decision trees, and support vector machines. Image classification is used in areas such as medical imaging, image retrieval, and content-based indexing.

Image Processing: Image processing is the manipulation and analysis of digital images. It involves techniques such as image enhancement, restoration, compression, and segmentation. Image processing is used in areas such as photography, video processing, and computer vision.

Object Detection: Object detection is the process of identifying and locating objects in images or videos. It involves techniques such as convolutional neural networks, bounding boxes, and region-based methods. Object detection is used in areas such as security, surveillance, and autonomous systems.

Semantic Segmentation: Semantic segmentation is the process of dividing an image into different semantic regions, such as objects, backgrounds, and foreground. It involves techniques such as convolutional neural networks, deep learning, and graph-based methods. Semantic segmentation is used in areas such as medical imaging, autonomous vehicles, and scene understanding.

Human Pose Estimation: Human pose estimation is the process of estimating the pose of a human body in images or videos. It involves techniques such as deep learning, 3D reconstruction, and motion tracking. Human pose estimation is used in areas such as augmented reality, virtual reality, and human-computer interaction.

Stereo Vision: Stereo vision is the process of generating a 3D view of a scene from two or more images. It involves techniques such as disparity estimation, feature matching, and triangulation. Stereo vision is used in areas such as autonomous vehicles, 3D imaging, and surveillance.

Computational Photography: Computational photography is the use of computer algorithms to enhance or modify images or videos. It involves techniques such as image optimization, color correction, and image synthesis. Computational photography is used in areas such as photography, video editing, and computer vision.

Neural Networks: Neural networks are a type of artificial intelligence that mimics the behavior of the human brain. They involve a network of interconnected neurons that learn and adapt to data. Neural networks are used in areas such as image recognition, speech recognition, and natural language processing.

Image Coding: Image coding is the process of compressing digital images to reduce their size without losing quality. It involves techniques such as JPEG, PNG, and JPEG 2000. Image coding is used in areas such as image transmission, storage, and web browsing.

Image Reconstruction: Image reconstruction is the process of restoring an image from a set of noisy or incomplete data. It involves techniques such as interpolation, deconvolution, and regularization. Image reconstruction is used in areas such as medical imaging, astronomy, and remote sensing.

Object Recognition: Object recognition is the process of identifying and categorizing objects in images or videos. It involves techniques such as feature extraction, classification, and tracking. Object recognition is used in areas such as security, surveillance, and autonomous systems.

Motion Estimation: Motion estimation is the process of estimating the motion of objects in images or videos. It involves techniques such as optical flow, motion tracking, and particle filters. Motion estimation is used in areas such as video surveillance, sports analysis, and robotics.

The 17th European Conference on Computer Vision (ECCV 2022) in Tel Aviv, Israel, brought together a diverse community of researchers and practitioners from around the world to explore the latest advancements in computer vision. With a total of 1645 papers presented, the conference covered a wide 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 conference featured a mix of keynote lectures, invited talks, and technical sessions, where researchers presented their latest findings and discussed the challenges and opportunities in the field. The papers covered a wide range of topics, from traditional computer vision algorithms to cutting-edge machine learning techniques, and from theoretical developments to practical applications.

One of the key themes of the conference was the integration of computer vision with other fields such as artificial intelligence, robotics, and healthcare. Researchers showcased how computer vision can be used to improve the performance of autonomous systems, enable natural language processing, and assist in medical imaging and diagnosis.

Another important aspect of the conference was the emphasis on interdisciplinary collaboration and the exchange of ideas between different research communities. The conference brought together researchers from computer science, mathematics, engineering, and other fields, fostering a rich environment for collaboration and innovation.

The conference also featured a number of workshops and tutorials, providing opportunities for researchers to learn about new techniques and tools in the field. These workshops were led by experts in the field and covered a wide range of topics, from deep learning to computer vision applications in healthcare.

Overall, the 17th European Conference on Computer Vision was a successful event that showcased the latest advancements in computer vision and provided a platform for researchers and practitioners to exchange ideas and collaborate. The conference's proceedings, which will be published in the LNCS series, will serve as a valuable resource for the field and will contribute to the ongoing development of computer vision.

The 17th European Conference on Computer Vision (ECCV 2022) in Tel Aviv, Israel, was a remarkable event that brought together a diverse community of researchers and practitioners from around the world to explore the latest advancements in computer vision. With a total of 1645 papers presented, the conference covered a wide 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 conference featured a mix of keynote lectures, invited talks, and technical sessions, where researchers presented their latest findings and discussed the challenges and opportunities in the field. The papers covered a wide range of topics, from traditional computer vision algorithms to cutting-edge machine learning techniques, and from theoretical developments to practical applications.

One of the key themes of the conference was the integration of computer vision with other fields such as artificial intelligence, robotics, and healthcare. Researchers showcased how computer vision can be used to improve the performance of autonomous systems, enable natural language processing, and assist in medical imaging and diagnosis.

Another important aspect of the conference was the emphasis on interdisciplinary collaboration and the exchange of ideas between different research communities. The conference brought together researchers from computer science, mathematics, engineering, and other fields, fostering a rich environment for collaboration and innovation.

The conference also featured a number of workshops and tutorials, providing opportunities for researchers to learn about new techniques and tools in the field. These workshops were led by experts in the field and covered a wide range of topics, from deep learning to computer vision applications in healthcare.

Overall, the 17th European Conference on Computer Vision was a successful event that showcased the latest advancements in computer vision and provided a platform for researchers and practitioners to exchange ideas and collaborate. The conference's proceedings, which will be published in the LNCS series, will serve as a valuable resource for the field and will contribute to the ongoing development of computer vision.

Weight: 1211g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031200700
Edition number: 1st ed. 2022