Roey Mechrez

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 6 papers; trusts 901 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 192 citations into it; #4,932 of 21,575 by trust here, #6,371 by citations
• Media Technology — 95 citations into it
• Generative Models — 71 citations into it
• Evaluation & Benchmarks — 31 citations into it; #2,891 of 3,147 by trust here, #2,275 by citations
• Computational Mechanics — 17 citations into it
• Artificial Intelligence — 13 citations into it; #11,936 of 35,345 by trust here, #18,586 by citations
• Computer Graphics and Computer-Aided Design — 11 citations into it
• Optimization & Training — 10 citations into it

Whom Roey Mechrez trusts overall

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

1. Karen Simonyan
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Kaiming He
5. Alex Krizhevsky
6. Andrew Zisserman
7. Yoshua Bengio
8. Yann LeCun
9. Ross B. Girshick
10. Jimmy Ba

Who trusts Roey Mechrez overall

1. Yochai Blau
2. Yi Wang
3. Muhammad Waleed Gondal
4. Tomer Michaeli
5. Tamar Rott Shaham
6. Subeesh Vasu
7. Wenming Yang
8. Itamar Talmi
9. Xin Tao
10. Lihi Zelnik-Manor

Papers from Roey Mechrez's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
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

• The Contextual Loss for Image Transformation with Non-Aligned Data (2018) — 421 citations
• Maintaining Natural Image Statistics with the Contextual Loss (2018) — 104 citations
• 2018 PIRM Challenge on Perceptual Image Super-resolution (2018) — 545 citations
• Template Matching with Deformable Diversity Similarity (2016) — 105 citations
• The 2018 PIRM Challenge on Perceptual Image Super-Resolution (2018) — 94 citations
• Learning to Maintain Natural Image Statistics (2018) — 33 citations