{"product_id":"computer-vision-eccv-2022-workshops-tel-aviv-israel-october-2327-2022-proceedings-part-v-9783031250712","title":"Computer Vision - ECCV 2022 Workshops: Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part V","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThe 8-volume set of the LNCS books 13801-13809 contains the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022, in Tel Aviv, Israel. The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the conference proceedings, covering various topics in computer vision, such as AI for space, vision for art, adversarial robustness, autonomous vehicle vision, learning with limited and imperfect data, medical computer vision, metaverse, self-supervised learning, and more. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 774 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 18 February 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003eThe 8-volume set, comprising the LNCS books 13801 until 13809, represents the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision (ECCV), ECCV 2022. This prestigious conference took place in Tel Aviv, Israel, from October 23 to 27, 2022, with the workshops being conducted in a hybrid or online format.\u003cbr\u003e\u003cbr\u003eWithin this comprehensive volume set, there are 367 full papers that have undergone meticulous review and selection for inclusion in the ECCV 2022 workshop proceedings. These papers are organized into six distinct parts, each focusing on a specific area of computer vision research.\u003cbr\u003e\u003cbr\u003ePart I: AI for Space, W01, explores the application of artificial intelligence (AI) in space exploration and satellite imaging. It delves into topics such as autonomous navigation, object detection, and image analysis in space environments.\u003cbr\u003e\u003cbr\u003ePart II: Vision for Art, W02, focuses on the use of computer vision for artistic purposes, including image manipulation, content creation, and artistic expression. It explores techniques such as generative art, facial recognition, and scene understanding.\u003cbr\u003e\u003cbr\u003ePart III: Adversarial Robustness in the Real World, W03, addresses the challenges of robustness in computer vision systems when faced with adversarial attacks. It explores techniques for defending against adversarial examples and improving the generalization ability of vision models.\u003cbr\u003e\u003cbr\u003ePart IV: Autonomous Vehicle Vision, W04, explores the use of computer vision in autonomous vehicles, including object detection, scene understanding, and navigation. It discusses the latest developments in self-driving technology and the potential applications of computer vision in transportation.\u003cbr\u003e\u003cbr\u003ePart V: Self-Supervised Learning: What Is Next?, W09, examines the latest advancements in self-supervised learning, a powerful technique for learning from unlabeled data. It covers topics such as unsupervised feature learning, autoencoders, and generative models.\u003cbr\u003e\u003cbr\u003ePart VI: AI for Creative Video Editing and Understanding, W16, explores the use of AI in creative video editing and understanding. It discusses techniques such as video summarization, scene detection, and emotion recognition in video content.\u003cbr\u003e\u003cbr\u003ePart VII: Visual Inductive Priors for Data-Efficient Deep Learning, W17, investigates the use of visual inductive priors in deep learning models. It explores the benefits of using visual cues for improving the accuracy and efficiency of deep learning algorithms.\u003cbr\u003e\u003cbr\u003ePart VIII: Mobile Intelligent Photography and Imaging, W18, focuses on the use of mobile devices for intelligent photography and imaging. It explores topics such as image enhancement, object detection, and scene understanding in mobile applications.\u003cbr\u003e\u003cbr\u003ePart IX: People Analysis: From Face, Body, and Fashion to 3D Virtual Avatars, W19, explores the use of computer vision for analyzing human faces, bodies, and fashion. It discusses techniques such as facial recognition, body pose estimation, and virtual avatar generation.\u003cbr\u003e\u003cbr\u003ePart X: Safe Artificial Intelligence for Automated Driving, W20, addresses the safety concerns associated with autonomous driving. It explores techniques for detecting and avoiding obstacles, predicting the behavior of other vehicles, and ensuring safe and reliable autonomous driving systems.\u003cbr\u003e\u003cbr\u003ePart XI: Real-World Surveillance: Applications and Challenges, W21, explores the applications of computer vision in real-world surveillance systems. It discusses topics such as object detection, face recognition, and scene understanding in surveillance applications.\u003cbr\u003e\u003cbr\u003ePart XII: Affective Behavior Analysis In-the-Wild, W22, focuses on the analysis of affective behavior in natural environments. It explores techniques such as emotion recognition, facial expression analysis, and body posture analysis.\u003cbr\u003e\u003cbr\u003ePart XIII: Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark, W23, explores the use of computer vision for human pose estimation and navigation in human environments. It discusses the JackRabbot human body pose dataset and its applications in human-robot interaction and navigation.\u003cbr\u003e\u003cbr\u003ePart XIV: Distributed Smart Cameras, W24, focuses on the use of distributed smart cameras for surveillance and monitoring applications. It discusses the design and implementation of distributed camera networks and their applications in various scenarios.\u003cbr\u003e\u003cbr\u003ePart XV: Causality in Visi, W25, explores the use of computer vision for understanding causality in visual scenes. It discusses techniques such as scene parsing, event recognition, and causal inference algorithms.\u003cbr\u003e\u003cbr\u003eIn conclusion, the 8-volume set of the ECCV 2022 workshop proceedings, comprising the LNCS books 13801 until 13809, represents a comprehensive collection of cutting-edge research in computer vision. These papers cover a wide range of topics, from AI for space exploration to self-supervised learning and autonomous vehicle vision. The meticulous review process ensures that only the most innovative and significant contributions are included, making this volume set a valuable resource for researchers, practitioners, and students in the field.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1205g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031250712\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2023\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44304003825914,"sku":"9783031250712","price":72.58,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_34453b1e-6367-4c06-9121-22c433d65e53.jpg?v=1688020402","url":"https:\/\/shulphink.com\/products\/computer-vision-eccv-2022-workshops-tel-aviv-israel-october-2327-2022-proceedings-part-v-9783031250712","provider":"Shulph Ink","version":"1.0","type":"link"}