{"product_id":"computer-vision-eccv-2022-17th-european-conference-tel-aviv-israel-october-2327-2022-proceedings-part-xxxviii-9783031198380","title":"Computer Vision - ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXXVIII","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: 23 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.\u003cbr\u003e\u003cbr\u003eImage Classification: Image classification algorithms are used to categorize images based on their content, such as objects, landscapes, or animals.\u003cbr\u003e\u003cbr\u003eImage Processing: Image processing algorithms are used to enhance, modify, and analyze images, such as cropping, resizing, and color correction.\u003cbr\u003e\u003cbr\u003eObject Detection: Object detection algorithms are used to identify and locate objects in images and videos.\u003cbr\u003e\u003cbr\u003eSemantic Segmentation: Semantic segmentation algorithms are used to divide an image into different regions or objects based on their semantic meaning.\u003cbr\u003e\u003cbr\u003eHuman Pose Estimation: Human pose estimation algorithms are used to determine the position and orientation of human bodies in images and videos.\u003cbr\u003e\u003cbr\u003eStereo Vision: Stereo vision algorithms are used to create 3D reconstructions of scenes from multiple camera views.\u003cbr\u003e\u003cbr\u003eComputational Photography: Computational photography algorithms are used to enhance and manipulate images captured by cameras.\u003cbr\u003e\u003cbr\u003eNeural Networks: Neural networks are a type of artificial intelligence algorithm that mimics the behavior of the human brain.\u003cbr\u003e\u003cbr\u003eImage Coding: Image coding algorithms are used to compress and encode images for storage and transmission.\u003cbr\u003e\u003cbr\u003eImage Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data.\u003cbr\u003e\u003cbr\u003eObject Recognition: Object recognition algorithms are used to identify and classify objects in images and videos.\u003cbr\u003e\u003cbr\u003eMotion Estimation: Motion estimation algorithms are used to estimate the motion of objects in images and videos.\u003cbr\u003e\u003cbr\u003eThese proceedings represent the latest advancements in computer vision research and provide a valuable resource for researchers, practitioners, and students in the field.\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 diverse community of researchers, practitioners, and industry experts from around the world to explore the latest developments and advancements in computer vision.\u003cbr\u003e\u003cbr\u003eThe conference featured a wide range of technical sessions, workshops, and tutorials, covering a broad spectrum 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.\u003cbr\u003e\u003cbr\u003eImage Classification: Image classification algorithms are used to categorize images based on their content, such as objects, landscapes, or animals.\u003cbr\u003e\u003cbr\u003eImage Processing: Image processing algorithms are used to enhance, modify, and analyze images, such as cropping, resizing, and color correction.\u003cbr\u003e\u003cbr\u003eObject Detection: Object detection algorithms are used to identify and locate objects in images and videos.\u003cbr\u003e\u003cbr\u003eSemantic Segmentation: Semantic segmentation algorithms are used to divide an image into different regions or objects based on their semantic meaning.\u003cbr\u003e\u003cbr\u003eHuman Pose Estimation: Human pose estimation algorithms are used to determine the position and orientation of human bodies in images and videos.\u003cbr\u003e\u003cbr\u003eStereo Vision: Stereo vision algorithms are used to create 3D reconstructions of scenes from multiple camera views.\u003cbr\u003e\u003cbr\u003eComputational Photography: Computational photography algorithms are used to enhance and manipulate images captured by cameras.\u003cbr\u003e\u003cbr\u003eNeural Networks: Neural networks are a type of artificial intelligence algorithm that mimics the behavior of the human brain.\u003cbr\u003e\u003cbr\u003eImage Coding: Image coding algorithms are used to compress and encode images for storage and transmission.\u003cbr\u003e\u003cbr\u003eImage Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data.\u003cbr\u003e\u003cbr\u003eObject Recognition: Object recognition algorithms are used to identify and classify objects in images and videos.\u003cbr\u003e\u003cbr\u003eMotion Estimation: Motion estimation algorithms are used to estimate the motion of objects in images and videos.\u003cbr\u003e\u003cbr\u003eThe conference also included a number of keynote speeches and invited talks by prominent researchers in the field, providing valuable insights and perspectives on the current state-of-the-art in computer vision.\u003cbr\u003e\u003cbr\u003eIn total, the 17th ECCV 2022 received a record number of submissions, with over 5,800 papers submitted from around the globe. The review process was rigorous, with each paper being evaluated by a panel of expert reviewers from academia and industry. The accepted papers were published in the 39-volume set of the Lecture Notes in Computer Science (LNCS) series, covering a wide range of topics in computer vision.\u003cbr\u003e\u003cbr\u003eThe conference was a great success, with attendees from various countries and backgrounds coming together to share their knowledge and expertise in computer vision. The conference provided a platform for researchers to showcase their work, network with colleagues, and learn about the latest research and developments in the field.\u003cbr\u003e\u003cbr\u003eOverall, the 17th ECCV 2022 was a landmark event in the field of computer vision, and it played a significant role in advancing the state-of-the-art in this rapidly evolving field. The conference's success was a testament to the hard work and dedication of the organizers, reviewers, and participants, and it is expected to continue to be a major event in the years to come.\u003cbr\u003e\u003cbr\u003eThe 17th European Conference on Computer Vision (ECCV) 2022, held in Tel Aviv, Israel, from October 23 to 27, 2022, was a remarkable event that brought together a diverse community of researchers, practitioners, and industry experts from around the world to explore the latest developments and advancements in computer vision.\u003cbr\u003e\u003cbr\u003eThe conference featured a wide range of technical sessions, workshops, and tutorials, covering a broad spectrum 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.\u003cbr\u003e\u003cbr\u003eImage Classification: Image classification algorithms are used to categorize images based on their content, such as objects, landscapes, or animals.\u003cbr\u003e\u003cbr\u003eImage Processing: Image processing algorithms are used to enhance, modify, and analyze images, such as cropping, resizing, and color correction.\u003cbr\u003e\u003cbr\u003eObject Detection: Object detection algorithms are used to identify and locate objects in images and videos.\u003cbr\u003e\u003cbr\u003eSemantic Segmentation: Semantic segmentation algorithms are used to divide an image into different regions or objects based on their semantic meaning.\u003cbr\u003e\u003cbr\u003eHuman Pose Estimation: Human pose estimation algorithms are used to determine the position and orientation of human bodies in images and videos.\u003cbr\u003e\u003cbr\u003eStereo Vision: Stereo vision algorithms are used to create 3D reconstructions of scenes from multiple camera views.\u003cbr\u003e\u003cbr\u003eComputational Photography: Computational photography algorithms are used to enhance and manipulate images captured by cameras.\u003cbr\u003e\u003cbr\u003eNeural Networks: Neural networks are a type of artificial intelligence algorithm that mimics the behavior of the human brain.\u003cbr\u003e\u003cbr\u003eImage Coding: Image coding algorithms are used to compress and encode images for storage and transmission.\u003cbr\u003e\u003cbr\u003eImage Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data.\u003cbr\u003e\u003cbr\u003eObject Recognition: Object recognition algorithms are used to identify and classify objects in images and videos.\u003cbr\u003e\u003cbr\u003eMotion Estimation: Motion estimation algorithms are used to estimate the motion of objects in images and videos.\u003cbr\u003e\u003cbr\u003eThe conference also included a number of keynote speeches and invited talks by prominent researchers in the field, providing valuable insights and perspectives on the current state-of-the-art in computer vision.\u003cbr\u003e\u003cbr\u003eIn total, the 17th ECCV 2022 received a record number of submissions, with over 5,800 papers submitted from around the globe. The review process was rigorous, with each paper being evaluated by a panel of expert reviewers from academia and industry. The accepted papers were published in the 39-volume set of the Lecture Notes in Computer Science (LNCS) series, covering a wide range of topics in computer vision.\u003cbr\u003e\u003cbr\u003eThe conference was a great success, with attendees from various countries and backgrounds coming together to share their knowledge and expertise in computer vision. The conference provided a platform for researchers to showcase their work, network with colleagues, and learn about the latest research and developments in the field.\u003cbr\u003e\u003cbr\u003eOverall, the 17th ECCV 2022 was a landmark event in the field of computer vision, and it played a significant role in advancing the state-of-the-art in this rapidly evolving field. The conference's success was a testament to the hard work and dedication of the organizers, reviewers, and participants, and it is expected to continue to be a major event in the years to come.\u003cbr\u003e\u003cbr\u003eThe 17th European Conference on Computer Vision (ECCV) 2022, held in Tel Aviv, Israel, from October 23 to 27, 2022, was a remarkable event that brought together a diverse community of researchers, practitioners, and industry experts from around the world to explore the latest developments and advancements in computer vision.\u003cbr\u003e\u003cbr\u003eThe conference featured a wide range of technical sessions, workshops, and tutorials, covering a broad spectrum 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.\u003cbr\u003e\u003cbr\u003eImage Classification: Image classification algorithms are used to categorize images based on their content, such as objects, landscapes, or animals.\u003cbr\u003e\u003cbr\u003eImage Processing: Image processing algorithms are used to enhance, modify, and analyze images, such as cropping, resizing, and color correction.\u003cbr\u003e\u003cbr\u003eObject Detection: Object detection algorithms are used to identify and locate objects in images and videos.\u003cbr\u003e\u003cbr\u003eSemantic Segmentation: Semantic segmentation algorithms are used to divide an image into different regions or objects based on their semantic meaning.\u003cbr\u003e\u003cbr\u003eHuman Pose Estimation: Human pose estimation algorithms are used to determine the position and orientation of human bodies in images and videos.\u003cbr\u003e\u003cbr\u003eStereo Vision: Stereo vision algorithms are used to create 3D reconstructions of scenes from multiple camera views.\u003cbr\u003e\u003cbr\u003eComputational Photography: Computational photography algorithms are used to enhance and manipulate images captured by cameras.\u003cbr\u003e\u003cbr\u003eNeural Networks: Neural networks are a type of artificial intelligence algorithm that mimics the behavior of the human brain.\u003cbr\u003e\u003cbr\u003eImage Coding: Image coding algorithms are used to compress and encode images for storage and transmission.\u003cbr\u003e\u003cbr\u003eImage Reconstruction: Image reconstruction algorithms are used to recreate images from incomplete or corrupted data.\u003cbr\u003e\u003cbr\u003eObject Recognition: Object recognition algorithms are used to identify and classify objects in images and videos.\u003cbr\u003e\u003cbr\u003eMotion Estimation: Motion estimation algorithms are used to estimate the motion of objects in images and videos.\u003cbr\u003e\u003cbr\u003eThe conference also included a number of keynote speeches and invited talks by prominent researchers in the field, providing valuable insights and perspectives on the current state-of-the-art in computer vision.\u003cbr\u003e\u003cbr\u003eIn total, the 17th ECCV 2022 received a record number of submissions, with over 5,800 papers submitted from around the globe. The review process was rigorous, with each paper being evaluated by a panel of expert reviewers from academia and industry. The accepted papers were published in the 39-volume set of the Lecture Notes in Computer Science (LNCS) series, covering a wide range of topics in computer vision.\u003cbr\u003e\u003cbr\u003eThe conference was a great success, with attendees from various countries and backgrounds coming together to share their knowledge and expertise in computer vision. The conference provided a platform for researchers to showcase their work, network with colleagues, and learn about the latest research and developments in the field.\u003cbr\u003e\u003cbr\u003eOverall, the 17th ECCV 2022 was a landmark event in the field of computer vision, and it played a significant role in advancing the state-of-the-art in this rapidly evolving field. The conference's success was a testament to the hard work and dedication of the organizers, reviewers, and participants, and it is expected to continue to be a major event in the years to come.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1240g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031198380\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":45290376757498,"sku":"9783031198380","price":85.39,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_bd989733-6e73-418b-af9e-ef87a9d88b52.jpg?v=1706343323","url":"https:\/\/shulphink.com\/products\/computer-vision-eccv-2022-17th-european-conference-tel-aviv-israel-october-2327-2022-proceedings-part-xxxviii-9783031198380","provider":"Shulph Ink","version":"1.0","type":"link"}