| Description |
1 online resource (xxvi, 774 pages) : illustrations (some color) |
| Series |
Lecture notes in computer science, 1611-3349 ; 13805 |
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Lecture notes in computer science ; 13805. 1611-3349
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| Contents |
Intro -- Foreword -- Preface -- Organization -- Contents - Part V -- W18 -- Challenge on Mobile Intelligent Photography and Imaging -- W18 -- Challenge on Mobile Intelligent Photography and Imaging -- MIPI 2022 Challenge on RGB+ToF Depth Completion: Dataset and Report*-4pt -- 1 Introduction -- 2 Challenge -- 2.1 Problem Definition -- 2.2 Dataset: TetrasRGBD -- 2.3 Challenge Phases -- 2.4 Scoring System -- 2.5 Running Time Evaluation -- 3 Challenge Results -- 4 Challenge Methods -- 4.1 ZoomNeXt -- 4.2 GAMEON -- 4.3 Singer -- 4.4 NPU-CVR -- 4.5 JingAM -- 4.6 Anonymous -- 4.7 MainHouse113 |
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4.8 UCLA Vision Lab -- 5 Conclusions -- A Teams and Affiliations -- References -- MIPI 2022 Challenge on Quad-Bayer Re-mosaic: Dataset and Report -- 1 Introduction -- 2 Challenge -- 2.1 Problem Definition -- 2.2 Dataset: Tetras-Quad -- 2.3 Challenge Phases -- 2.4 Scoring System -- 3 Challenge Results -- 4 Challenge Methods -- 4.1 MegNR -- 4.2 IMEC-IPI & NPU-MPI -- 4.3 HITZST01 -- 4.4 BITSpectral -- 4.5 JHC-SJTU -- 4.6 Op-summer-po -- 5 Conclusions -- A Teams and Affiliations -- References -- MIPI 2022 Challenge on RGBW Sensor Re-mosaic: Dataset and Report -- 1 Introduction -- 2 Challenge |
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2.1 Problem Definition -- 2.2 Dataset: Tetras-RGBW-RMSC -- 2.3 Challenge Phases -- 2.4 Scoring System -- 3 Challenge Results -- 4 Challenge Methods -- 4.1 Op-summer-po -- 4.2 HIT-IIL -- 4.3 Eating, Drinking and Playing -- 5 Conclusions -- A Teams and Affiliations -- References -- MIPI 2022 Challenge on RGBW Sensor Fusion: Dataset and Report -- 1 Introduction -- 2 Challenge -- 2.1 Problem Definition -- 2.2 Dataset: Tetras-RGBW-Fusion -- 2.3 Challenge Phases -- 2.4 Scoring System -- 3 Challenge Results -- 4 Challenge Methods -- 4.1 BITSpectral -- 4.2 BIVLab -- 4.3 HIT-IIL -- 4.4 Jzsherlock |
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4.5 LLCKP -- 4.6 MegNR -- 5 Conclusions -- A Teams and Affiliations -- References -- MIPI 2022 Challenge on Under-Display Camera Image Restoration: Methods and Results -- 1 Introduction -- 2 MIPI 2022 Under-Display Camera Image Restoration -- 2.1 Datasets -- 2.2 Evaluation -- 2.3 Challenge Phase -- 3 Challenge Results -- 4 Challenge Methods and Teams -- 5 Conclusions -- References -- Continuous Spectral Reconstruction from RGB Images via Implicit Neural Representation -- 1 Introduction -- 2 Related Work -- 2.1 Implicit Neural Representation -- 2.2 Spectral Reconstruction from RGB Images |
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3 Neural Spectral Reconstruction -- 3.1 Overview -- 3.2 Spectral Profile Interpolation -- 3.3 Neural Attention Mapping -- 3.4 Loss Function -- 4 Experiments -- 4.1 Comparison to State-of-the-Art Methods -- 4.2 Continuous Spectral Reconstruction -- 4.3 Extreme Spectral Reconstruction -- 4.4 Spectral Super Resolution -- 4.5 Ablation Studies -- 5 Conclusion -- References -- Event-Based Image Deblurring with Dynamic Motion Awareness -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 System Overview -- 3.2 Deblur Module -- 3.3 Multi-scale Coarse-to-Fine Approach -- 3.4 Loss Function |
| Summary |
The 8-volume set, comprising the LNCS books 13801 until 13809, constitutes the refereed proceedings of 38 out of the 60 workshops held at the 17th European Conference on Computer Vision, ECCV 2022. The conference took place in Tel Aviv, Israel, during October 23-27, 2022; the workshops were held hybrid or online. The 367 full papers included in this volume set were carefully reviewed and selected for inclusion in the ECCV 2022 workshop proceedings. They were organized in individual parts as follows: Part I: W01 - AI for Space; W02 - Vision for Art; W03 - Adversarial Robustness in the Real World; W04 - Autonomous Vehicle Vision Part II: W05 - Learning With Limited and Imperfect Data; W06 - Advances in Image Manipulation; Part III: W07 - Medical Computer Vision; W08 - Computer Vision for Metaverse; W09 - Self-Supervised Learning: What Is Next?; Part IV: W10 - Self-Supervised Learning for Next-Generation Industry-Level Autonomous Driving; W11 - ISIC Skin Image Analysis; W12 - Cross-Modal Human-Robot Interaction; W13 - Text in Everything; W14 - BioImage Computing; W15 - Visual Object-Oriented Learning Meets Interaction: Discovery, Representations, and Applications; W16 - AI for Creative Video Editing and Understanding; W17 - Visual Inductive Priors for Data-Efficient Deep Learning; W18 - Mobile Intelligent Photography and Imaging; Part V: W19 - People Analysis: From Face, Body and Fashion to 3D Virtual Avatars; W20 - Safe Artificial Intelligence for Automated Driving; W21 - Real-World Surveillance: Applications and Challenges; W22 - Affective Behavior Analysis In-the-Wild; Part VI: W23 - Visual Perception for Navigation in Human Environments: The JackRabbot Human Body Pose Dataset and Benchmark; W24 - Distributed Smart Cameras; W25 - Causality in Vision; W26 - In-Vehicle Sensing and Monitorization; W27 - Assistive Computer Vision and Robotics; W28 - Computational Aspects of Deep Learning; Part VII: W29 - Computer Vision for Civil and Infrastructure Engineering; W30 - AI-Enabled Medical Image Analysis: Digital Pathology and Radiology/COVID19; W31 - Compositional and Multimodal Perception; Part VIII: W32 - Uncertainty Quantification for Computer Vision; W33 - Recovering 6D Object Pose; W34 - Drawings and Abstract Imagery: Representation and Analysis; W35 - Sign Language Understanding; W36 - A Challenge for Out-of-Distribution Generalization in Computer Vision; W37 - Vision With Biased or Scarce Data; W38 - Visual Object Tracking Challenge. |
| Notes |
Includes author index |
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Online resource; title from PDF title page (SpringerLink, viewed February 20, 2023) |
| Subject |
Computer vision -- Congresses
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Pattern recognition systems -- Congresses
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Computer vision
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Pattern recognition systems
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| Genre/Form |
proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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| Form |
Electronic book
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| Author |
Karlinsky, Leonid, editor
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Michaeli, Tomer, editor.
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Nishino, Ko, editor.
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| ISBN |
9783031250729 |
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3031250729 |
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