Julien N. P. Martel

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 2 papers; trusts 95 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 75 citations into it; #8,167 of 21,575 by trust here, #5,754 by citations
• Computer Graphics and Computer-Aided Design — 37 citations into it; #942 of 1,584 by trust here, #950 by citations
• Computational Mechanics — 36 citations into it; #5,875 of 10,001 by trust here, #5,567 by citations
• 3D Vision & Pose — 25 citations into it
• Generative Models — 21 citations into it
• Model Architectures — 10 citations into it

Whom Julien N. P. Martel trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Yoshua Bengio
6. Ola Marius Lysaker
7. Vincent Sitzmann
8. Yann LeCun
9. Matan Atzmon
10. Ilya Sutskever

Who trusts Julien N. P. Martel overall

1. Zong-Yi Li
2. Geoffrey E. Hinton
3. Alex Yu
4. Matthew Tancik
5. Nikola B. Kovachki
6. Songyou Peng
7. Cheng Sun
8. Christian Reiser
9. Chien-Yao Wang
10. Yinbo Chen

Papers from Julien N. P. Martel's perspective

Ordered by how strongly the researchers Julien N. P. Martel 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Implicit Neural Representations with Periodic Activation Functions (2020) — 3,729 citations
• AutoInt: Automatic Integration for Fast Neural Volume Rendering (2020) — 297 citations