Jack Valmadre

Computer Vision and Pattern Recognition · 2015–2018

A researcher in the Science corpus: 8 papers; trusts 709 researchers and is trusted by 856 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 272 citations into it; #1,469 of 21,575 by trust here, #1,294 by citations
• Artificial Intelligence — 45 citations into it
• Aerospace Engineering — 33 citations into it
• Global and Planetary Change — 19 citations into it
• Electrical and Electronic Engineering — 17 citations into it
• Biomedical Engineering — 11 citations into it
• Optimization & Training — 11 citations into it
• Model Architectures — 10 citations into it

Whom Jack Valmadre trusts overall

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

1. Martin Danelljan
2. Alex Krizhevsky
3. Kaiming He
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Ross B. Girshick
7. Ilya Sutskever
8. Yoshua Bengio
9. Yann LeCun
10. Andrew Zisserman

Who trusts Jack Valmadre overall

1. Martin Danelljan
2. Bo Li
3. Qiang Wang
4. Ning Wang
5. Zhipeng Zhang
6. Heng Fan
7. Luca Bertinetto
8. Tianyu Yang
9. Xingping Dong
10. Goutam Bhat

Papers from Jack Valmadre's perspective

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

Their papers

• Fully-Convolutional Siamese Networks for Object Tracking (2016) — 4,373 citations
• Learning feed-forward one-shot learners (2016) — 494 citations
• The Visual Object Tracking VOT2015 Challenge Results (2015) — 901 citations
• The Visual Object Tracking VOT2016 Challenge Results (2016) — 773 citations
• Staple: Complementary Learners for Real-Time Tracking (2015) — 1,648 citations
• End-to-End Representation Learning for Correlation Filter Based Tracking (2017) — 1,460 citations
• The Sixth Visual Object Tracking VOT2018 Challenge Results (2018) — 797 citations
• Dense Semantic Correspondence Where Every Pixel is a Classifier (2015) — 57 citations