Indexing billions of images for sketch-based retrieval
By Xing Sun, Changhu Wang, Chao Xu, Lei Zhang. 2013
59 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Information Retrieval & Search
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Jun-Yan Zhu
- Ling Shao
- Alexei A. Efros
- Eli Shechtman
- Fumin Shen
- Yuming Shen
- Philipp Krahenbuhl
- Li Liu
In Computer Vision and Pattern Recognition
- Ling Shao
- Dacheng Tao
- Luc Van Gool
- Ming-Hsuan Yang
- Alan L. Yuille
- Tao A. Xiang
- Alexei A. Efros
- Trevor Darrell
In Information Retrieval & Search
- Ling Shao
- Fumin Shen
- Yuming Shen
- Toshihiko Yamasaki
- Kiyoharu Aizawa
- Alexei A. Efros
- Eli Shechtman
- Philipp Krahenbuhl
Citations in the corpus
- Generative Visual Manipulation on the Natural Image Manifold (2016, background): “The difference with previous sketch-to-image retrieval methods [41] or AverageExplorer [42], is that due to potentially contradicting user constraints, the result may look very different than any single image from the dataset or an average of such images, and more of a realistic hybrid image [43].”
- Deep Sketch Hashing: Fast Free-Hand Sketch-Based Image Retrieval (2017, methodology): “Inspired by this, some recent SBIR works [1, 15, 43, 56, 58, 60] have incorporated existing hashing methods for efficient retrieval.”
- Sketch-based manga retrieval using manga109 dataset (2015, methodology): “In the manga feature description task, we compared the proposed method with (1) BoF, (2) large-window FV as the state-of-the-art of BoF-based methods [5], and (3) compact oriented chamfer matching (Compact OCM) as the state-of-the-art of chamfer-based methods [4].”