Varun Ramakrishna

Computer Vision and Pattern Recognition · 2012–2016

A researcher in the Science corpus: 4 papers; trusts 327 researchers and is trusted by 1,962 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 84 citations into it; #899 of 21,575 by trust here, #2,253 by citations
• Artificial Intelligence — 18 citations into it; #3,097 of 35,345 by trust here, #3,797 by citations
• Human-Computer Interaction — 13 citations into it; #1,036 of 2,253 by trust here, #523 by citations
• Biomedical Engineering — 11 citations into it
• Computational Mechanics — 11 citations into it
• Model Architectures — 10 citations into it
• Control and Systems Engineering — 9 citations into it; #974 of 8,257 by trust here, #1,252 by citations
• 3D Vision & Pose — 8 citations into it; #91 of 689 by trust here, #69 by citations

Whom Varun Ramakrishna trusts overall

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

1. Yoshua Bengio
2. Mykhaylo Andriluka
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Pedro F. Felzenszwalb
6. Yann LeCun
7. Kaiming He
8. Deva Ramanan
9. Jerome H. Friedman
10. Ilya Sutskever

Who trusts Varun Ramakrishna overall

1. Grégory Rogez
2. Francesc Moreno-Noguer
3. Xiaowei Zhou
4. Angjoo Kanazawa
5. Michael J. Black
6. Xingyi Zhou
7. Georgios Pavlakos
8. Zhe Cao
9. Juergen Gall
10. Kaiming He

Papers from Varun Ramakrishna's perspective

Ordered by how strongly the researchers Varun Ramakrishna 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Convolutional Pose Machines (2016) — 2,922 citations
• Reconstructing 3D Human Pose from 2D Image Landmarks (2012) — 338 citations
• Pose Machines: Articulated Pose Estimation via Inference Machines (2014) — 263 citations
• User-Specific Hand Modeling from Monocular Depth Sequences (2014) — 101 citations