Pascal Mettes

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 4 papers; trusts 733 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 96 citations into it; #8,428 of 21,575 by trust here, #11,498 by citations
• Artificial Intelligence — 53 citations into it; #16,964 of 35,345 by trust here, #20,377 by citations
• Representation & Self-Supervised Learning — 16 citations into it; #2,443 of 3,145 by trust here, #2,863 by citations
• Evaluation & Benchmarks — 12 citations into it
• Model Architectures — 9 citations into it; #1,822 of 2,278 by trust here, #2,078 by citations
• Biomedical Engineering — 6 citations into it

Whom Pascal Mettes trusts overall

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

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

Who trusts Pascal Mettes overall

1. Tianhao Li
2. Xirong Li
3. Dima Damen
4. Davide Moltisanti
5. Jianfeng Dong
6. Alexander Richard
7. Philippe Weinzaepfel
8. Tianyu Gao
9. Guilhem Chéron
10. Limin Wang

Papers from Pascal Mettes's perspective

Ordered by how strongly the researchers Pascal Mettes 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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Spot On: Action Localization from Pointly-Supervised Proposals (2016) — 127 citations
• The ImageNet Shuffle: Reorganized Pre-training for Video Event Detection (2016) — 123 citations
• Hyperspherical Prototype Networks (2019) — 161 citations
• Spatial-Aware Object Embeddings for Zero-Shot Localization and Classification of Actions (2017) — 94 citations