Lluis Gomez i Bigorda

Computer Vision and Pattern Recognition · 2013–2021

A researcher in the Science corpus: 5 papers; trusts 332 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 103 citations into it; #8,085 of 21,575 by trust here, #2,976 by citations
• Artificial Intelligence — 43 citations into it
• Multimodal Learning — 28 citations into it; #1,052 of 1,211 by trust here, #862 by citations
• Evaluation & Benchmarks — 24 citations into it; #2,113 of 3,147 by trust here, #1,217 by citations
• Natural Language Processing — 17 citations into it
• Representation & Self-Supervised Learning — 16 citations into it; #2,836 of 3,145 by trust here, #2,148 by citations
• Model Architectures — 7 citations into it
• Media Technology — 5 citations into it

Whom Lluis Gomez i Bigorda trusts overall

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

1. Ross B. Girshick
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yoshua Bengio
6. Kaiming He
7. Yann LeCun
8. Ilya Sutskever
9. Jia Deng
10. Ronald J. Williams

Who trusts Lluis Gomez i Bigorda overall

1. Minghui Liao
2. Mert Bulent Sariyildiz
3. Pengyuan Lyu
4. Xue Yang
5. Mathilde Caron
6. Cong Yao
7. Ali Furkan Biten
8. Diangang Li
9. Baoguang Shi
10. Xiang Bai

Papers from Lluis Gomez i Bigorda's perspective

Ordered by how strongly the researchers Lluis Gomez i Bigorda 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. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• ICDAR 2013 Robust Reading Competition (2013) — 1,473 citations
• ICDAR 2015 competition on Robust Reading (2015) — 1,578 citations
• Self-Supervised Learning of Visual Features through Embedding Images into Text Topic Spaces (2017) — 130 citations
• Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning (2021) — 98 citations
• Improving patch-based scene text script identification with ensembles of conjoined networks (2016) — 79 citations