Jorge Sánchez
Computer Vision and Pattern Recognition · 2010–2013
A researcher in the Science corpus: 7 papers; trusts 811 researchers and is trusted by 9,371 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 171 citations into it; #195 of 21,575 by trust here, #1,000 by citations
- Artificial Intelligence — 50 citations into it; #638 of 35,345 by trust here, #2,453 by citations
- Media Technology — 36 citations into it; #409 of 3,621 by trust here, #452 by citations
- Aerospace Engineering — 28 citations into it; #325 of 6,421 by trust here, #478 by citations
- Information Retrieval & Search — 27 citations into it; #174 of 1,022 by trust here, #300 by citations
- Representation & Self-Supervised Learning — 22 citations into it; #761 of 3,145 by trust here, #1,068 by citations
- Evaluation & Benchmarks — 21 citations into it
- Statistical Learning Theory — 16 citations into it
Whom Jorge Sánchez trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Florent Perronnin
- Herv'e J'egou
- Cordelia Schmid
- Andrew Zisserman
- Yann LeCun
- Geoffrey E. Hinton
- Andrea Vedaldi
- Alex Krizhevsky
- Svetlana Lazebnik
Who trusts Jorge Sánchez overall
- Florent Perronnin
- Andrew Zisserman
- Andrea Vedaldi
- Karen Simonyan
- Zeynep Akata
- Yi Yang
- Lingxi Xie
- Cordelia Schmid
- Limin Wang
- Luc Van Gool
Papers from Jorge Sánchez's perspective
Ordered by how strongly the researchers Jorge Sánchez trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Improving the Fisher Kernel for Large-Scale Image Classification (2010) — 2,882 citations
- Aggregating Local Image Descriptors into Compact Codes (2012) — 1,660 citations
- Author manuscript, published in "International Journal of Computer Vision (2013)" International Journal of Computer Vision manuscript No. (will be inserted by the editor) Image Classification with the Fisher Vector: Theory and Practice (2013) — 1,235 citations
- Large-scale image retrieval with compressed Fisher vectors (2010) — 864 citations
- High-dimensional signature compression for large-scale image classification (2011) — 362 citations
- Large-scale image categorization with explicit data embedding (2010) — 182 citations
- Modeling the spatial layout of images beyond spatial pyramids (2012) — 122 citations