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Inpainting and Denoising Challenges
The problem of dealing with missing or incomplete data in machine learning and computer vision arises in many applications. Recent strategies make use of generative models to impute missing or corrupted data. Advances in computer vision using deep generative models have found applications in image/video processing, such as denoising, restoration, super-resolution, or inpainting. Inpainting and Denoising Challenges comprises recent efforts dealing with image and video inpainting tasks. This includes winning solutions to the ChaLearn Looking at People inpainting and denoising challenges: human pose recovery, video de-captioning and fingerprint restoration. This volume starts with a wide review...
Multimodal Technologies for Perception of Humans
This book constitutes the thoroughly refereed joint post-workshop proceedings of two co-located events: the Second International Workshop on Classification of Events, Activities and Relationships, CLEAR 2007, and the 5th Rich Transcription 2007 Meeting Recognition evaluation, RT 2007, held in succession in Baltimore, MD, USA, in May 2007. The workshops had complementary evaluation efforts; CLEAR for the evaluation of human activities, events, and relationships in multiple multimodal data domains; and RT for the evaluation of speech transcription-related technologies from meeting room audio collections. The 35 revised full papers presented from CLEAR 2007 cover 3D person tracking, 2D face detection and tracking, person and vehicle tracking on surveillance data, vehicle and person tracking aerial videos, person identification, head pose estimation, and acoustic event detection. The 15 revised full papers presented from RT 2007 are organized in topical sections on speech-to-text, and speaker diarization.
The Moving Image Workshop
If you need a fun, hands-on introduction to core animation techniques - then look no further! Heather Freeman guides you through a wide range of practical projects, helping you establish and build skills in narrative animation, motion graphics and visual effects. Each chapter begins by summarizing historical and theoretical concerns and connecting them with current practice and applications - all beautifully illustrated with stills from classic commercial and independent films, as well as contemporary examples from student work. Having established this context, the remainder of the chapter focuses on walking readers through their own creative projects. Topics covered include early animation technologies and techniques, scenes and staging, character animation, animated type, visual effects and motion graphics, pre- through post-production and experimental approaches to motion graphics. Dozens of sample files are available online, for experimentation and to get readers started on each exercise. The companion website also includes example animations as well as links to recommended software tutorials, recommended artist websites, blogs and animation channels.
The Loneliest Americans
A “provocative and sweeping” (Time) blend of family history and original reportage that explores—and reimagines—Asian American identity in a Black and white world “[Kang’s] exploration of class and identity among Asian Americans will be talked about for years to come.”—Jennifer Szalai, The New York Times Book Review (Editors’ Choice) ONE OF THE BEST BOOKS OF THE YEAR: Time, NPR, Mother Jones In 1965, a new immigration law lifted a century of restrictions against Asian immigrants to the United States. Nobody, including the lawmakers who passed the bill, expected it to transform the country’s demographics. But over the next four decades, millions arrived, including Jay Casp...
Advanced Methods and Deep Learning in Computer Vision
Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. - Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field - Illustrates principles with modern, real-world applications - Suitable for self-learning or as a text for graduate courses
Computer Vision - ACCV 2006
These volumes present together a total of 64 revised full papers and 128 revised posters papers. The papers are organized in topical sections on camera calibration, stereo and pose, texture, face recognition, variational methods, tracking, geometry and calibration, lighting and focus, in the first volume. The papers of the second volume cover topics as detection and applications, statistics and kernels, segmentation, geometry and statistics, signal processing, and video processing.
