Dense Image Correspondences for Computer Vision PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Dense Image Correspondences for Computer Vision PDF full book. Access full book title Dense Image Correspondences for Computer Vision by Tal Hassner. Download full books in PDF and EPUB format.
Author: Tal Hassner Publisher: Springer ISBN: 3319230484 Category : Technology & Engineering Languages : en Pages : 302
Book Description
This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems.
Author: Tal Hassner Publisher: Springer ISBN: 3319230484 Category : Technology & Engineering Languages : en Pages : 302
Book Description
This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems.
Author: Xueting Li Publisher: ISBN: Category : Languages : en Pages : 234
Book Description
Correspondence is ubiquitous in our visual world. It describes the relationship of two images by pointing out which parts in one image relate to which parts in the other image. It is the fundamental task in many computer vision applications. For instance, object tracking essentially studies the correspondence of different parts on the same object through time, while semantic segmentation links the same semantic parts of different objects through space. Furthermore, the study of correspondence facilitates many applications such as structure from motion or label propagation through video frames. However, correspondence annotation is notoriously hard to harvest. Existing work either utilize synthesized data (e.g., optical flow from a game engine) or other human annotations (e.g., semantic segmentation), leading to domain limitation or tedious human efforts. My research focuses on learning and applying correspondence in computer vision tasks in a self-supervised manner to resolve these limitations. I start by introducing a method that learns reliable dense correspondence from videos in a self-supervised manner. Next, I discuss two methods that utilize correspondence between images or video frames to facilitate 3D mesh reconstruction. To begin with, I present a work that learns a self-supervised, single-view 3D reconstruction model that predicts the 3D mesh shape, texture, and camera pose of a target object with a collection of 2D images and silhouettes. Then, based on the two methods discussed above, the intuitive question is that can we combine the correspondence learned in the first work and the mesh reconstruction model in the second work to solve mesh reconstruction from video frames? Thus, in the last work, I demonstrate an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild.
Author: Gennady E. Zaikov Publisher: CRC Press ISBN: 1498707734 Category : Science Languages : en Pages : 532
Book Description
This new book facilitates the study of problematic chemicals in such applications as chemical fate modeling, chemical process design, and experimental design. It provides a valuable overview of current chemical processes, products, and practices and analyzes theories to formulate and prove physicochemical principles. It addresses the production and
Author: B. Uma Shankar Publisher: Springer ISBN: 3319699008 Category : Computers Languages : en Pages : 705
Book Description
This book constitutes the proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2017,held in Kolkata, India, in December 2017. The total of 86 full papers presented in this volume were carefully reviewed and selected from 293 submissions. They were organized in topical sections named: pattern recognition and machine learning; signal and image processing; computer vision and video processing; soft and natural computing; speech and natural language processing; bioinformatics and computational biology; data mining and big data analytics; deep learning; spatial data science and engineering; and applications of pattern recognition and machine intelligence.
Author: Seghir Maamir Publisher: CRC Press ISBN: 1498714102 Category : Science Languages : en Pages : 338
Book Description
Understanding chemical and solid materials and their properties and behavior is fundamental to chemical and engineering design. With some of the world's leading experts describing their most recent research, this book describes the procedures for material selection and design to ensure that the most suitable materials for a given application are id
Author: Shai Avidan Publisher: Springer Nature ISBN: 3031200802 Category : Computers Languages : en Pages : 815
Book Description
The 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. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as 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.
Author: Andrew Fitzgibbon Publisher: Springer ISBN: 3642337120 Category : Computers Languages : en Pages : 901
Book Description
The seven-volume set comprising LNCS volumes 7572-7578 constitutes the refereed proceedings of the 12th European Conference on Computer Vision, ECCV 2012, held in Florence, Italy, in October 2012. The 408 revised papers presented were carefully reviewed and selected from 1437 submissions. The papers are organized in topical sections on geometry, 2D and 3D shapes, 3D reconstruction, visual recognition and classification, visual features and image matching, visual monitoring: action and activities, models, optimisation, learning, visual tracking and image registration, photometry: lighting and colour, and image segmentation.
Author: David Forsyth Publisher: Springer Science & Business Media ISBN: 3540886893 Category : Computers Languages : en Pages : 841
Book Description
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
Author: Tal Hassner
Author: Tal Hassner
Author: Xueting Li
Author: Miao Wang
Author: Gennady E. Zaikov
Author: B. Uma Shankar
Author: Seghir Maamir
Author: Shai Avidan
Author: Andrew Fitzgibbon
Author: Aleš Leonardis
Author: David Forsyth