Abel Gonzalez-Garcia

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 7 papers; trusts 850 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 290 citations into it; #7,995 of 21,575 by trust here, #4,245 by citations
• Artificial Intelligence — 85 citations into it; #15,972 of 35,345 by trust here, #10,798 by citations
• Generative Models — 67 citations into it; #1,093 of 1,956 by trust here, #973 by citations
• Evaluation & Benchmarks — 41 citations into it
• Representation & Self-Supervised Learning — 28 citations into it; #2,587 of 3,145 by trust here, #2,691 by citations
• Safety, Risk, Reliability and Quality — 21 citations into it
• Aerospace Engineering — 18 citations into it
• Biophysics — 14 citations into it

Whom Abel Gonzalez-Garcia trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Ross B. Girshick
4. Yann LeCun
5. Kaiming He
6. Diederik P. Kingma
7. Yoshua Bengio
8. Karen Simonyan
9. Ilya Sutskever
10. David G. Lowe

Who trusts Abel Gonzalez-Garcia overall

1. Edo Collins
2. Liqian Ma
3. Yash Goyal
4. Miaoyun Zhao
5. Qicheng Lao
6. Bolei Zhou
7. Sergey I. Nikolenko
8. Nupur Kumari
9. Martin Danelljan
10. Radhakrishna Achanta

Papers from Abel Gonzalez-Garcia's perspective

Ordered by how strongly the researchers Abel Gonzalez-Garcia 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. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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

• Transferring GANs: generating images from limited data (2018) — 320 citations
• MineGAN: Effective Knowledge Transfer From GANs to Target Domains With Few Images (2019) — 208 citations
• Image-to-image translation for cross-domain disentanglement (2018) — 260 citations
• Do Semantic Parts Emerge in Convolutional Neural Networks? (2016) — 118 citations
• The Sixth Visual Object Tracking VOT2018 Challenge Results (2018) — 797 citations
• Learning the Model Update for Siamese Trackers (2019) — 385 citations
• The Seventh Visual Object Tracking VOT2019 Challenge Results (2019) — 486 citations