{"product_id":"computer-vision-eccv-2022-17th-european-conference-tel-aviv-israel-october-2327-2022-proceedings-part-xxxiv-9783031198298","title":"Computer Vision - ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXXIV","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThe 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. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 763 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 22 October 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe 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.\u003cbr\u003e\u003cbr\u003eThe 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:\u003cbr\u003e\u003cbr\u003eComputer Vision: This field encompasses the development and application of algorithms for tasks such as image analysis, object detection, and scene understanding.\u003cbr\u003e\u003cbr\u003eMachine Learning: Machine learning algorithms are used to analyze and interpret data, enabling computers to make predictions and decisions based on patterns.\u003cbr\u003e\u003cbr\u003eDeep 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.\u003cbr\u003e\u003cbr\u003eReinforcement Learning: Reinforcement learning involves training agents to make decisions in complex environments by receiving feedback in the form of rewards or penalties.\u003cbr\u003e\u003cbr\u003eObject 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.\u003cbr\u003e\u003cbr\u003eImage Classification: Image classification algorithms are used to categorize images based on their content, such as flowers, animals, or buildings.\u003cbr\u003e\u003cbr\u003eImage Processing: Image processing algorithms are used to enhance, modify, and analyze images, enabling tasks such as image restoration and image compression.\u003cbr\u003e\u003cbr\u003eObject Detection: Object detection algorithms are used to identify and locate objects in images and videos, enabling applications such as security surveillance and autonomous navigation.\u003cbr\u003e\u003cbr\u003eSemantic Segmentation: Semantic segmentation algorithms are used to segment images into different regions based on their semantic content, such as objects, backgrounds, or faces.\u003cbr\u003e\u003cbr\u003eHuman Pose Estimation: Human pose estimation algorithms are used to estimate the pose of a human body in images or videos, enabling applications such as virtual reality and human-computer interaction.\u003cbr\u003e\u003cbr\u003eThree-Dimensional Reconstruction: Three-dimensional reconstruction algorithms are used to create three-dimensional models of objects and scenes from two-dimensional images or videos.\u003cbr\u003e\u003cbr\u003eStereo Vision: Stereo vision algorithms are used to create depth perception and 3D reconstructions from multiple camera images.\u003cbr\u003e\u003cbr\u003eComputational Photography: Computational photography algorithms are used to enhance and manipulate images and videos using computer vision techniques.\u003cbr\u003e\u003cbr\u003eNeural 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.\u003cbr\u003e\u003cbr\u003eImage 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.\u003cbr\u003e\u003cbr\u003eImage Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data, enabling tasks such as medical imaging and satellite imaging.\u003cbr\u003e\u003cbr\u003eObject 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.\u003cbr\u003e\u003cbr\u003eMotion 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.\u003cbr\u003e\u003cbr\u003eThese proceedings represent the latest advancements in computer vision research and technology, covering a wide range of applications and domains. The contributions of the authors and reviewers have significantly contributed to the progress of this field, and we hope that these proceedings will be valuable to researchers, practitioners, and students alike.\u003cbr\u003e\u003cbr\u003eThe 17th European Conference on Computer Vision (ECCV) 2022, held in Tel Aviv, Israel, from October 23 to 27, 2022, brought together a vibrant community of researchers and practitioners in the field of computer vision. The conference featured a wide range of technical presentations, workshops, and tutorials, covering the latest advancements in computer vision research and applications.\u003cbr\u003e\u003cbr\u003eThe conference proceedings, spanning 39 volumes and covering LNCS books 13661 to 13699, represent the refereed proceedings of the conference. The papers presented at ECCV 2022 were subjected to a rigorous review process, with a total of 5804 submissions received. From these submissions, a select group of 1645 papers were accepted for presentation at the conference.\u003cbr\u003e\u003cbr\u003eThe conference proceedings cover a diverse range of topics in computer vision, including:\u003cbr\u003e\u003cbr\u003eComputer Vision: This field encompasses the development and application of algorithms for tasks such as image analysis, object detection, and scene understanding. The papers presented at ECCV 2022 covered a wide range of topics in computer vision, including object recognition, image classification, and scene interpretation.\u003cbr\u003e\u003cbr\u003eMachine Learning: Machine learning algorithms are used to analyze and interpret data, enabling computers to make predictions and decisions based on patterns. The papers presented at ECCV 2022 covered a wide range of machine learning techniques, including deep learning, convolutional neural networks, and reinforcement learning.\u003cbr\u003e\u003cbr\u003eDeep 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. The papers presented at ECCV 2022 covered a wide range of deep neural network architectures, training techniques, and applications.\u003cbr\u003e\u003cbr\u003eReinforcement Learning: Reinforcement learning involves training agents to make decisions in complex environments by receiving feedback in the form of rewards or penalties. The papers presented at ECCV 2022 covered a wide range of reinforcement learning algorithms, including policy optimization, value learning, and imitation learning.\u003cbr\u003e\u003cbr\u003eObject 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. The papers presented at ECCV 2022 covered a wide range of object recognition techniques, including feature extraction, classifiers, and deep learning.\u003cbr\u003e\u003cbr\u003eImage Classification: Image classification algorithms are used to categorize images based on their content, such as flowers, animals, or buildings. The papers presented at ECCV 2022 covered a wide range of image classification techniques, including convolutional neural networks, decision trees, and transfer learning.\u003cbr\u003e\u003cbr\u003eImage Processing: Image processing algorithms are used to enhance, modify, and analyze images, enabling tasks such as image restoration and image compression. The papers presented at ECCV 2022 covered a wide range of image processing techniques, including image enhancement, denoising, and segmentation.\u003cbr\u003e\u003cbr\u003eObject Detection: Object detection algorithms are used to identify and locate objects in images and videos, enabling applications such as security surveillance and autonomous navigation. The papers presented at ECCV 2022 covered a wide range of object detection techniques, including convolutional neural networks, YOLO, and SSD.\u003cbr\u003e\u003cbr\u003eSemantic Segmentation: Semantic segmentation algorithms are used to segment images into different regions based on their semantic content, such as objects, backgrounds, or faces. The papers presented at ECCV 2022 covered a wide range of semantic segmentation techniques, including convolutional neural networks, U-Net, and Fully Convolutional Networks.\u003cbr\u003e\u003cbr\u003eHuman Pose Estimation: Human pose estimation algorithms are used to estimate the pose of a human body in images or videos, enabling applications such as virtual reality and human-computer interaction. The papers presented at ECCV 2022 covered a wide range of human pose estimation techniques, including 3D pose estimation, 2D pose estimation, and multi-view pose estimation.\u003cbr\u003e\u003cbr\u003eThree-Dimensional Reconstruction: Three-dimensional reconstruction algorithms are used to create three-dimensional models of objects and scenes from two-dimensional images or videos. The papers presented at ECCV 2022 covered a wide range of three-dimensional reconstruction techniques, including photogrammetry, point cloud processing, and depth estimation.\u003cbr\u003e\u003cbr\u003eStereo Vision: Stereo vision algorithms are used to create depth perception and 3D reconstructions from multiple camera images. The papers presented at ECCV 2022 covered a wide range of stereo vision techniques, including stereo matching, disparity estimation, and 3D reconstruction.\u003cbr\u003e\u003cbr\u003eComputational Photography: Computational photography algorithms are used to enhance and manipulate images and videos using computer vision techniques. The papers presented at ECCV 2022 covered a wide range of computational photography techniques, including image enhancement, color correction, and scene reconstruction.\u003cbr\u003e\u003cbr\u003eNeural Networks: Neural networks are a class of algorithms that are inspired by the structure and function of the human brain. The papers presented at ECCV 2022 covered a wide range of neural network architectures, training techniques, and applications.\u003cbr\u003e\u003cbr\u003eImage 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. The papers presented at ECCV 2022 covered a wide range of image coding techniques, including JPEG, PNG, and JPEG2000.\u003cbr\u003e\u003cbr\u003eImage Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data, enabling tasks such as medical imaging and satellite imaging. The papers presented at ECCV 2022 covered a wide range of image reconstruction techniques, including image inpainting, super-resolution, and denoising.\u003cbr\u003e\u003cbr\u003eObject 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. The papers presented at ECCV 2022 covered a wide range of object recognition techniques, including convolutional neural networks, deep learning, and transfer learning.\u003cbr\u003e\u003cbr\u003eMotion 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. The papers presented at ECCV 2022 covered a wide range of motion estimation techniques, including optical flow, particle filters, and deep learning.\u003cbr\u003e\u003cbr\u003eThe conference proceedings provide a valuable resource for researchers, practitioners, and students in the field of computer vision. The papers presented at ECCV 2022 cover a wide range of topics and represent the latest advancements in computer vision research and technology. The contributions of the authors and reviewers have significantly contributed to the progress of this field, and we hope that these proceedings will be valuable to researchers, practitioners, and students alike.\u003cbr\u003e\u003cbr\u003eIn conclusion, the 17th European Conference on Computer Vision (ECCV) 2022 was a resounding success, bringing together a diverse community of researchers and practitioners in the field of computer vision. The conference proceedings, spanning 39 volumes and covering LNCS books 13661 to 13699, represent the refereed proceedings of the conference and provide a valuable resource for researchers, practitioners, and students in the field. The papers presented at ECCV 2022 cover a wide range of topics in 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 contributions of the authors and reviewers have significantly contributed to the progress of this field, and we hope that these proceedings will be valuable to researchers, practitioners, and students alike.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1234g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031198298\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":45290376626426,"sku":"9783031198298","price":85.39,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_6e1965d4-8910-41f1-90ea-ca05f0e0b8be.jpg?v=1706343328","url":"https:\/\/shulphink.com\/products\/computer-vision-eccv-2022-17th-european-conference-tel-aviv-israel-october-2327-2022-proceedings-part-xxxiv-9783031198298","provider":"Shulph Ink","version":"1.0","type":"link"}