Francesco Ragusa

Computer Vision and Pattern Recognition · 2019–2023

A researcher in the Science corpus: 4 papers; trusts 732 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 221 citations into it; #19,694 of 21,575 by trust here, #17,258 by citations
• Artificial Intelligence — 84 citations into it
• Evaluation & Benchmarks — 35 citations into it; #2,735 of 3,147 by trust here, #2,853 by citations
• Human-Computer Interaction — 27 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Model Architectures — 13 citations into it
• Signal Processing — 10 citations into it
• Computational Mechanics — 6 citations into it

Whom Francesco Ragusa trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Andrew Zisserman
4. Karen Simonyan
5. Alex Krizhevsky
6. Geoffrey E. Hinton
7. Christoph Feichtenhofer
8. Jitendra Malik
9. Yann LeCun
10. Ilya Sutskever

Who trusts Francesco Ragusa overall

1. Antonino Furnari
2. Giovanni Maria Farinella
3. Ahmad Darkhalil

Papers from Francesco Ragusa's perspective

Ordered by how strongly the researchers Francesco Ragusa 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain (2020) — 138 citations
• Egocentric Visitors Localization in Cultural Sites (2019) — 29 citations
• Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives (2023) — 529 citations
• MECCANO: A Multimodal Egocentric Dataset for Humans Behavior Understanding in the Industrial-like Domain (2022) — 59 citations