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

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: 729 pages
Publication date: 23 October 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 encompasses the study of computer systems for understanding and interpreting visual data, such as images, videos, and 3D scenes. It involves techniques such as image processing, pattern recognition, and object detection.

Machine Learning: Machine learning is a branch of computer science that involves the development of algorithms that can learn from data and make predictions or decisions without being explicitly programmed. It is widely used in computer vision for tasks such as image classification, object detection, and facial recognition.

Deep Neural Networks: Deep neural networks are a type of neural network that consists of multiple layers of interconnected neurons. They are capable of learning complex patterns in data and have been used successfully in tasks 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. Agents in reinforcement learning receive rewards or penalties for their actions and use this feedback to improve their performance over time.

Object Recognition: Object recognition is the task of identifying and categorizing objects in images or videos. It involves techniques such as feature extraction, classification, and tracking.

Image Classification: Image classification is the task 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 Processing: Image processing is the manipulation of images to enhance their appearance, remove noise, or perform other operations. It involves techniques such as image enhancement, filtering, and segmentation.

Object Detection: Object detection is the task of identifying and locating objects in images or videos. It involves techniques such as convolutional neural networks, bounding boxes, and region-based methods.

Semantic Segmentation: Semantic segmentation is the task of dividing an image into different regions based on its semantic content. It involves techniques such as convolutional neural networks and deep learning.

Human Pose Estimation: Human pose estimation is the task of estimating the pose of a human body in an image or video. It involves techniques such as deep learning and computer vision.

Three-Dimensional Reconstruction: Three-dimensional reconstruction is the task of reconstructing a 3D scene from a set of 2D images or videos. It involves techniques such as photogrammetry and depth perception.

Stereo Vision: Stereo vision is the task of determining the depth and distance of objects in a scene using two or more cameras. It involves techniques such as disparity estimation and stereo matching.

Computational Photography: Computational photography is the use of computer algorithms to enhance or modify images captured by cameras. It involves techniques such as image optimization, color correction, and image synthesis.

Neural Networks: Neural networks are a type of artificial intelligence that mimics the behavior of the human brain. They are used in computer vision for tasks such as image recognition, object detection, and facial recognition.

Image Coding: Image coding is the process of compressing images to reduce their size without losing quality. It involves techniques such as JPEG compression, PNG compression, and lossless compression.

Image Reconstruction: Image reconstruction is the process of restoring an image that has been corrupted or degraded. It involves techniques such as image restoration, denoising, and deblurring.

Object Recognition: Object recognition is the task of identifying and categorizing objects in images or videos. It involves techniques such as feature extraction, classification, and tracking.

Motion Estimation: Motion estimation is the task of estimating the motion of objects in images or videos. It involves techniques such as optical flow, motion tracking, and particle filters.

The 17th European Conference on Computer Vision (ECCV) 2022 was a major event in the field of computer vision, bringing together researchers and practitioners from around the world to share their latest findings and advancements. The conference featured a wide range of technical sessions, workshops, and tutorials, covering a diverse range of topics in computer vision.

One of the highlights of the conference was the presentation of the Best Paper Award, which was given to the authors of the paper titled "DeepFusion: A Simple and Efficient Neural Image Fusion Method." The paper proposed a novel approach to image fusion that combines deep learning techniques with traditional image processing methods, resulting in improved image quality and reduced computational complexity.

Another notable aspect of the conference was the participation of prominent researchers and industry leaders in the field of computer vision. Keynote speakers included Professor Yann LeCun, the founder of Facebook's AI Research Lab, and Professor Yoshua Bengio, the co-founder of Google Brain. The conference also featured a number of invited talks by leading researchers in the field, who presented their latest research findings and discussed the future of computer vision.

In addition to the technical sessions, the conference also included a number of social events, such as a welcome reception, a conference dinner, and a poster session. These events provided opportunities for researchers and practitioners to network, exchange ideas, and build collaborations.

Overall, the 17th European Conference on Computer Vision (ECCV) 2022 was a successful event that showcased the latest advances in computer vision and provided a platform for researchers and practitioners to share their knowledge and expertise. The conference's proceedings, which are published in the LNCS series, will serve as a valuable resource for future research in the field.
The 17th European Conference on Computer Vision (ECCV) 2022, held in Tel Aviv, Israel, from October 23 to 27, 2022, was a significant event in the field of computer vision. With a total of 1645 papers presented, the conference showcased the latest research and advancements in various sub-fields of computer vision, 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 received a record number of submissions, with 5804 submissions from around the world. The papers were subjected to a rigorous review process, with each paper being evaluated by at least three expert reviewers. The selection process resulted in a high-quality conference program, featuring a mix of invited talks, oral presentations, and poster sessions.

One of the highlights of the conference was the presentation of the Best Paper Award, which was given to the authors of the paper titled "DeepFusion: A Simple and Efficient Neural Image Fusion Method." The paper proposed a novel approach to image fusion that combines deep learning techniques with traditional image processing methods, resulting in improved image quality and reduced computational complexity. The authors demonstrated the effectiveness of their method on a wide range of image fusion tasks, including medical image fusion, remote sensing image fusion, and video surveillance image fusion.

Another notable aspect of the conference was the participation of prominent researchers and industry leaders in the field of computer vision. Keynote speakers included Professor Yann LeCun, the founder of Facebook's AI Research Lab, and Professor Yoshua Bengio, the co-founder of Google Brain. The conference also featured a number of invited talks by leading researchers in the field, who presented their latest research findings and discussed the future of computer vision.

In addition to the technical sessions, the conference also included a number of social events, such as a welcome reception, a conference dinner, and a poster session. These events provided opportunities for researchers and practitioners to network, exchange ideas, and build collaborations.

Overall, the 17th European Conference on Computer Vision (ECCV) 2022 was a successful event that showcased the latest advances in computer vision and provided a platform for researchers and practitioners to share their knowledge and expertise. The conference's proceedings, which are published in the LNCS series, will serve as a valuable resource for future research in the field.

Weight: 1187g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031198410
Edition number: 1st ed. 2022