Locally-Transferred Fisher Vectors for Texture Classification

By Yang Song, Fan Zhang, Qing Li, Heng Huang, Lauren J. O'Donnell, Weidong (Tom) Cai. 2017

51 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

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. Xiaogang Wang
2. Luc Van Gool
3. Dacheng Tao
4. Trevor Darrell
5. Ming-Hsuan Yang
6. Ramalingam Chellappa
7. Cordelia Schmid
8. Andrew Zisserman

In Media Technology

1. Matti Pietikäinen
2. Paul W. Fieguth
3. Guoying Zhao
4. Jonathon Shlens
5. Quoc V. Le
6. Li Liu
7. Simon Kornblith
8. Jie Chen

Citations in the corpus

• Do Better ImageNet Models Transfer Better? (2018, methodology): “Several papers have proposed methods to make better use of CNN features and thus improve the efficacy of transfer learning [43, 11, 42, 23, 73, 63, 13, 41, 54].”
• From BoW to CNN: Two Decades of Texture Representation for Texture Classification (2018, methodology): “1) Traditional feature encoding and pooling; New pooling such as bilinear pooling [120, 123] and LFV [218]”