Max Argus

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 3 papers; trusts 107 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 38 citations into it; #18,161 of 21,575 by trust here, #10,677 by citations
• Reinforcement Learning — 35 citations into it; #1,287 of 2,242 by trust here, #1,241 by citations
• Artificial Intelligence — 34 citations into it
• Control and Systems Engineering — 14 citations into it; #6,913 of 8,257 by trust here, #2,147 by citations
• Optimization & Training — 13 citations into it
• Generative Models — 8 citations into it
• 3D Vision & Pose — 7 citations into it
• Model Architectures — 6 citations into it

Whom Max Argus trusts overall

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

1. Richard S. Sutton
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Andrew Barto
5. Leemon C. Baird III
6. Volodymyr Mnih
7. Sergey Ioffe
8. Alex Krizhevsky
9. Yoshua Bengio
10. Yann LeCun

Who trusts Max Argus overall

1. Alexander Sax
2. Timothée Lesort
3. Mengjiao Yang

Papers from Max Argus's perspective

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

Their papers

• FreiHAND: A Dataset for Markerless Capture of Hand Pose and Shape From Single RGB Images (2019) — 514 citations
• CrossNorm: Normalization for Off-Policy TD Reinforcement Learning (2019) — 32 citations
• Loss is its own Reward: Self-Supervision for Reinforcement Learning (2016) — 196 citations