SketchZooms: Deep Multi‐view Descriptors for Matching Line Drawings

Simple item page
dc.contributor.authorNavarro, Pabloen_US
dc.contributor.authorOrlando, J. Ignacioen_US
dc.contributor.authorDelrieux, Claudioen_US
dc.contributor.authorIarussi, Emmanuelen_US
dc.contributor.editorBenes, Bedrich and Hauser, Helwigen_US
dc.date.accessioned2021-02-27T19:02:32Z
dc.date.available2021-02-27T19:02:32Z
dc.date.issued2021
dc.description.abstractFinding point‐wise correspondences between images is a long‐standing problem in image analysis. This becomes particularly challenging for sketch images, due to the varying nature of human drawing style, projection distortions and viewport changes. In this paper, we present the first attempt to obtain a learned descriptor for dense registration in line drawings. Based on recent deep learning techniques for corresponding photographs, we designed descriptors to locally match image pairs where the object of interest belongs to the same semantic category, yet still differ drastically in shape, form, and projection angle. To this end, we have specifically crafted a data set of synthetic sketches using non‐photorealistic rendering over a large collection of part‐based registered 3D models. After training, a neural network generates descriptors for every pixel in an input image, which are shown togeneralize correctly in unseen sketches hand‐drawn by humans. We evaluate our method against a baseline of correspondences data collected from expert designers, in addition to comparisons with other descriptors that have been proven effective in sketches. Code, data and further resources will be publicly released by the time of publication.en_US
dc.description.number1
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume40
dc.identifier.doi10.1111/cgf.14197
dc.identifier.issn1467-8659
dc.identifier.pages410-423
dc.identifier.urihttps://doi.org/10.1111/cgf.14197
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14197
dc.publisher© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltden_US
dc.subjectimage and video processing
dc.subject2D morphing
dc.subjectimage and video processing
dc.subjectimage databases
dc.subjectimage and video processing
dc.titleSketchZooms: Deep Multi‐view Descriptors for Matching Line Drawingsen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
v40i1pp410-423.pdf
Size:
2.64 MB
Format:
Adobe Portable Document Format
Download
Collections
40-Issue 1