Efficient indexing for large scale visual search

By Xiao Zhang, Zhiwei Li, Lei Zhang, Wei-Ying Ma, Heung-Yeung Shum. 2009

Subfields: 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 Computer Vision and Pattern Recognition

1. Luc Van Gool
2. Jitendra Malik
3. Li Fei-Fei
4. Andrew Zisserman
5. Trevor Darrell
6. Dacheng Tao
7. Xiaogang Wang
8. Andrea Vedaldi

In Information Retrieval & Search

1. Li Fei-Fei
2. Ranjay Krishna
3. Florent Perronnin
4. Jorge Sánchez
5. Pushmeet Kohli
6. Michael S. Bernstein
7. Thomas Mensink
8. David A. Shamma

Citations in the corpus

• Aggregating Local Image Descriptors into Compact Codes (2012, neutral): “However, while the decomposition is explicit in [33], it is implicit in the FV case.”
• Learning to Navigate the Energy Landscape (2016, background): “Significant work on building efficient index that can be used by LSH include [50] where the authors propose a compounds representation by decomposing images into background and image-specific information.”
• Improving the Fisher Kernel for Large-Scale Image Classification (2010, background): “However, while the decomposition is explicit in [24], it is implicit in the FK case.”
• Image retrieval using scene graphs (2015, methodology): “Content-based image retrieval methods typically use low-level visual feature representations [50, 6], indexing [11, 69, 27, 28, 59], efficient sub-image search [38], object-category based retrieval [5, 62, 4], and other methods of modeling image similarity [52] to retrieve images based on their…”