Roee Litman

Computer Vision and Pattern Recognition · 2012–2017

A researcher in the Science corpus: 5 papers; trusts 188 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it; #5,209 of 21,575 by trust here, #9,079 by citations
• Computational Mechanics — 43 citations into it; #1,411 of 10,001 by trust here, #2,407 by citations
• Computer Graphics and Computer-Aided Design — 14 citations into it; #959 of 1,584 by trust here, #1,271 by citations
• Representation & Self-Supervised Learning — 12 citations into it; #2,045 of 3,145 by trust here, #2,587 by citations
• Aerospace Engineering — 7 citations into it

Whom Roee Litman trusts overall

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

1. A. Bronstein
2. Michael M. Bronstein
3. Facundo M'emoli
4. Ronald R. Coifman
5. Yaron Lipman
6. Mathieu Aubry
7. Marius Leordeanu
8. Vladimir G. Kim
9. Martin Reuter
10. Martial Hebert

Who trusts Roee Litman overall

1. Davide Boscaini
2. Jonathan Masci
3. Michael M. Bronstein
4. Emanuele Rodolà
5. Or Litany
6. Federico Monti
7. Silvia Biasotti
8. A. Bronstein
9. Nitika Verma
10. Tal Remez

Papers from Roee Litman's perspective

Ordered by how strongly the researchers Roee Litman 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. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
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

• Intrinsic shape context descriptors for deformable shapes (2012) — 179 citations
• Learning Spectral Descriptors for Deformable Shape Correspondence (2014) — 161 citations
• Product Manifold Filter: Non-rigid Shape Correspondence via Kernel Density Estimation in the Product Space (2017) — 139 citations
• Bayesian Inference of Bijective Non-Rigid Shape Correspondence (2016) — 11 citations
• Supervised Sparse Analysis and Synthesis Operators (2013) — 50 citations