Ariadna Quattoni
Computer Vision and Pattern Recognition · 2004–2009
A researcher in the Science corpus: 7 papers; trusts 413 researchers and is trusted by 4,949 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 42 citations into it; #418 of 21,575 by trust here, #1,719 by citations
- Artificial Intelligence — 24 citations into it; #4,963 of 35,345 by trust here, #5,834 by citations
- Media Technology — 12 citations into it; #52 of 3,621 by trust here, #219 by citations
- Representation & Self-Supervised Learning — 10 citations into it; #874 of 3,145 by trust here, #1,246 by citations
- Natural Language Processing — 9 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
- Signal Processing — 5 citations into it; #2,741 of 7,572 by trust here, #1,411 by citations
Whom Ariadna Quattoni trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Antonio Torralba
- Andrew McCallum
- Li Fei-Fei
- Rob Fergus
- Geoffrey E. Hinton
- John D. Lafferty
- Andrew Zisserman
- Alex Krizhevsky
- Pietro Perona
Who trusts Ariadna Quattoni overall
- Lingxi Xie
- Abhinav Kumar Gupta
- Bolei Zhou
- Rahaf Aljundi
- Yu-Xiong Wang
- Yangqing Jia
- Antonio Torralba
- Trevor Darrell
- Percy Liang
- Andrea Vedaldi
Papers from Ariadna Quattoni's perspective
Ordered by how strongly the researchers Ariadna Quattoni 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Recognizing indoor scenes (2009) — 1,785 citations
- Transfer learning for image classification with sparse prototype representations (2008) — 279 citations
- Hidden Conditional Random Fields (2007) — 564 citations
- Learning Visual Representations using Images with Captions (2007) — 133 citations
- Hidden Conditional Random Fields for Gesture Recognition (2006) — 562 citations
- Latent-Dynamic Discriminative Models for Continuous Gesture Recognition (2007) — 428 citations
- Conditional Random Fields for Object Recognition (2004) — 439 citations