Silvia Zuffi

Computer Vision and Pattern Recognition · 2013–2021

A researcher in the Science corpus: 3 papers; trusts 99 researchers and is trusted by 363 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 60 citations into it; #2,134 of 21,575 by trust here, #5,806 by citations
• Artificial Intelligence — 18 citations into it; #10,425 of 35,345 by trust here, #8,893 by citations
• 3D Vision & Pose — 11 citations into it
• Computational Mechanics — 10 citations into it
• Evaluation & Benchmarks — 10 citations into it

Whom Silvia Zuffi trusts overall

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

1. Michael J. Black
2. Geoffrey E. Hinton
3. L. V. D. van der Maaten
4. Matthew Maverick Loper
5. Olga Sorkine-Hornung
6. Thomas Joseph Cashman
7. Navneet Dalal
8. Alexander Weiss
9. Dragomir Anguelov
10. Federica Bogo

Who trusts Silvia Zuffi overall

1. Angjoo Kanazawa
2. Jitendra Malik
3. Limin Wang
4. Kiana Ehsani
5. Thibault Groueix
6. Minghua Liu
7. Saining Xie
8. Saurabh Gupta
9. Yu Qiao
10. Alexei A. Efros

Papers from Silvia Zuffi's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Et al
9. Histograms of oriented gradients for human detection
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Towards Understanding Action Recognition (2013) — 968 citations
• 3D Menagerie: Modeling the 3D Shape and Pose of Animals (2016) — 504 citations
• Perspectives in machine learning for wildlife conservation (2021) — 659 citations