Yanqiu Feng

Computer Vision and Pattern Recognition · 2014–2016

A researcher in the Science corpus: 3 papers; trusts 17 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Yanqiu Feng trusts

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Vladimir Katkovnik (in Computer Vision and Pattern Recognition)
  2. Karen O. Egiazarian (in Computer Vision and Pattern Recognition)
  3. Alessandro Foi (in Computer Vision and Pattern Recognition)
  4. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  5. John Ashburner (in Artificial Intelligence)
  6. Karl J. Friston (in Computer Vision and Pattern Recognition)
  7. Andrea Vedaldi (in Computer Vision and Pattern Recognition)
  8. Florent Perronnin (in Computer Vision and Pattern Recognition)
  9. Cordelia Schmid (in Computer Vision and Pattern Recognition)
  10. Karen Simonyan (in Computer Vision and Pattern Recognition)

Who trusts Yanqiu Feng

  1. Arvid Lundervold (in Computer Vision and Pattern Recognition)

Papers from Yanqiu Feng's perspective

Ordered by how strongly the researchers Yanqiu Feng trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
  2. Image quality assessment: from error visibility to structural similarity
  3. Video Google: a text retrieval approach to object matching in videos
  4. Improving the Fisher Kernel for Large-Scale Image Classification
  5. A Review of Image Denoising Algorithms, with a New One
  6. Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries (IEEE Transactions on Image Processing)
  7. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
  8. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  9. Vlfeat: an open and portable library of computer vision algorithms
  10. Nonlinear total variation based noise removal algorithms

Their papers