Itamar Talmi

Computer Vision and Pattern Recognition · 2016–2018

A researcher in the Science corpus: 4 papers; trusts 592 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 113 citations into it; #6,070 of 21,575 by trust here, #9,722 by citations
• Generative Models — 48 citations into it
• Media Technology — 36 citations into it
• Computational Mechanics — 16 citations into it
• Evaluation & Benchmarks — 14 citations into it
• Artificial Intelligence — 11 citations into it; #11,488 of 35,345 by trust here, #18,586 by citations
• Computer Graphics and Computer-Aided Design — 10 citations into it
• Optimization & Training — 10 citations into it

Whom Itamar Talmi trusts overall

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

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

Who trusts Itamar Talmi overall

1. Roey Mechrez
2. Yochai Blau
3. Yi Wang
4. Rotal Kat
5. Muhammad Waleed Gondal
6. Lihi Zelnik-Manor
7. Kfir Aberman
8. Wenming Yang
9. Tomer Michaeli
10. Subeesh Vasu

Papers from Itamar Talmi's perspective

Ordered by how strongly the researchers Itamar Talmi 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. Gradient-based learning applied to document recognition
5. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
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
• Template Matching with Deformable Diversity Similarity (2016) — 105 citations
• Learning to Maintain Natural Image Statistics (2018) — 33 citations