サクサク読めて、アプリ限定の機能も多数！
トップへ戻る
猛暑に注意を
graphics.cs.cmu.edu
http://graphics.cs.cmu.edu/projects/whatMakesParis/ What Makes Paris Look like Paris? People Carl Doersch Saurabh Singh Abhinav Gupta Josef Sivic Alexei A. Efros Abstract Given a large repository of geotagged imagery, we seek to automatically find visual elements, e.g. windows, balconies, and street signs, that are most distinctive for a certain geo-spatial area, for example the city of Paris. Thi
http://graphics.cs.cmu.edu/projects/crossDomainMatching/ Data-driven Visual Similarity for Cross-domain Image Matching Presented at SIGGRAPH Asia, 2011 People Abhinav Shrivastava Tomasz Malisiewicz Abhinav Gupta Alexei A. Efros A data-driven technique to find visual similarity which does not depend on any particular image domain or feature representation. Visit the webpage to see some cool results
People Jim McCann (Carnegie Mellon University) Nancy Pollard (Carnegie Mellon University) Abstract Photo-editing results. Before images are on the left. Source images from clayjar and P Doodle via flickr. We present an image editing program which allows artists to paint in the gradient domain with real-time feedback on megapixel-sized images. Along with a pedestrian, though powerful, gradient-pain
IM2GPS: estimating geographic information from a single image People James Hays Alexei Efros Abstract Estimating geographic information from an image is an excellent, difficult high-level computer vision problem whose time has come. The emergence of vast amounts of geographically-calibrated image data is a great reason for computer vision to start looking globally — on the scale of the entire plan
15-463 (15-862): Computational Photography (formerly: Rendering and Image Processing) Computer Science Department Carnegie Mellon University INSTRUCTOR: Alexei (Alyosha) Efros (Office hours: Tu 4:45-5:45pn) UNIVERSITY UNITS: 12 SEMESTER: Fall 2005 NEWSGROUP: cmu.cs.class.cs463 (read this for important information!) WEB PAGE: http://graphics.cs.cmu.edu/courses/15-463/ LOCATION: WeH 5419C TIME: TR 1
People James Hays Alexei Efros Abstract What can you do with a million images? In this paper we present a new image completion algorithm powered by a huge database of photographs gathered from the Web. The algorithm patches up holes in images by finding similar image regions in the database that are not only seamless but also semantically valid. Our chief insight is that while the space of images
The Carnegie Mellon Graphics Lab conducts cutting-edge research on computer graphics and computer vision, integrating insights from computer science, robotics, and mechanical engineering. Ioannis Gkioulekas recognized as Bodossaki Distinguished Young Scientist 19 June 2025 Yannis was selected as a 2025 Bodossaki Distinguished Young Scientist. Every two years, the Distinguished Young Scientist Awar
このページを最初にブックマークしてみませんか？
『Carnegie Mellon Computer Graphics』の新着エントリーを見る
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
