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Scene Completion Using Millions of Photographs
- http://graphics.cs.cmu.edu/projects/scene-completion
- none
Scene completion using millions of photographs | ACM …
- https://dl.acm.org/doi/10.1145/1276377.1276382
- 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 is effectively infinite ...
Scene completion using millions of photographs
- https://dl.acm.org/doi/10.1145/1400181.1400202
- 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 is effectively infinite ...
Scene Completion Using Millions of Photographs
- https://www.researchgate.net/publication/220425355_Scene_Completion_Using_Millions_of_Photographs
- Thus, the crucial step is the selection of source images from millions of images. The gist scene descriptor was introduced to select images depicting similar scenes in …
Scene Completion Using Millions of Photographs
- https://cacm.acm.org/magazines/2008/10/516-scene-completion-using-millions-of-photographs/fulltext?mobile=true?mobile=true?mobile=true?mobile=false
- Scene Completion Using Millions of Photographs. By James Hays, Alexei A. Efros Communications of the ACM, October 2008, Vol. 51 No. 10, Pages 87-94 ... Figure 1: Given an input image with a missing region, we use matching scenes from a large collection of photographs to complete the image.
Scene Completion Using Millions of Photographs
- https://www.slideserve.com/truly/scene-completion-using-millions-of-photographs
- Scene Completion Using Millions of Photographs. James Hays, Alexei A. Efros Carnegie Mellon University ACM SIGGRAPH 2007. Outline. Introduction Overview Semantic Scene Matching Local Context Matching Results and Comparison Conclusion. Outline. Introduction Overview Slideshow 5789885 by truly
GitHub - jiguanglizipao/scene-completion: A Scene …
- https://github.com/jiguanglizipao/scene-completion
- A Scene Completion Using Millions of Photographs Implementation - GitHub - jiguanglizipao/scene-completion: A Scene Completion Using Millions of Photographs ...
Scene Completion Using Millions of Photographs
- https://people.cs.pitt.edu/~kovashka/cs3710_sp15/bigdata_expts_jesse.pdf
- Datasets and Experiment… Experiment Pull out 2 images from database with respect to the categories identified by the CVCL database Beach, Open Country, Forest, Mountain, Highway, Street, City Center, Tall Building 1 of each from the CVCL subset; delete the originals in the compound dataset (s.t. we don’t find an exact match and replace with same image))
Scene Completion Using Millions of Photographs
- https://3dvar.com/Hays2007Scene.pdf
- Original Image Input Scene Matches Output Figure 1: Given an input image with a missing region, we use matching scenes from a large collection of photographs to complete the image. 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 ...
GitHub - charliec443/Scene-Completion: A Python …
- https://github.com/charliec443/Scene-Completion
- This is a naive Python implementation of Local Context Matching as shown in Scene Completion Using Millions of Photographs which was completed as part of Georgia Tech's Computational Photography Course. This repository contains the Jupyter notebook I worked off as well as the functions I used to generate the local context matching. More information of the approach can …
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