Sean Bell

Computer Vision and Pattern Recognition · 2013–2017

A researcher in the Science corpus: 7 papers; trusts 785 researchers and is trusted by 2,942 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 157 citations into it; #690 of 21,575 by trust here, #2,102 by citations
• Artificial Intelligence — 39 citations into it
• Evaluation & Benchmarks — 22 citations into it; #2,650 of 3,147 by trust here, #3,082 by citations
• Model Architectures — 21 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Media Technology — 13 citations into it; #1,361 of 3,621 by trust here, #910 by citations
• Computer Graphics and Computer-Aided Design — 12 citations into it; #1,187 of 1,584 by trust here, #760 by citations
• Aerospace Engineering — 9 citations into it

Whom Sean Bell trusts overall

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

1. Ross B. Girshick
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Kaiming He
5. Karen Simonyan
6. Yann LeCun
7. Yoshua Bengio
8. Ilya Sutskever
9. Andrew Zisserman
10. Christian Szegedy

Who trusts Sean Bell overall

1. Kaiming He
2. Liang-Chieh Chen
3. Abhinav Kumar Gupta
4. Iasonas Kokkinos
5. Wanli Ouyang
6. Bolei Zhou
7. X. Wang
8. Tsung-Yi Lin
9. Ross B. Girshick
10. Xiaogang Wang

Papers from Sean Bell's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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

• Inside-Outside Net: Detecting Objects in Context with Skip Pooling and Recurrent Neural Networks (2015) — 1,272 citations
• Material recognition in the wild with the Materials in Context Database (2014) — 578 citations
• OpenSurfaces (2013) — 145 citations
• Intrinsic images in the wild (2014) — 490 citations
• Learning visual similarity for product design with convolutional neural networks (2015) — 440 citations
• Learning Visual Clothing Style with Heterogeneous Dyadic Co-Occurrences (2015) — 333 citations
• Shading Annotations in the Wild (2017) — 71 citations