Ayan Sinha

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 7 papers; trusts 677 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 152 citations into it; #6,641 of 21,575 by trust here, #8,021 by citations
• Computational Mechanics — 63 citations into it; #1,489 of 10,001 by trust here, #1,671 by citations
• Artificial Intelligence — 53 citations into it; #30,612 of 35,345 by trust here, #27,551 by citations
• 3D Vision & Pose — 36 citations into it; #482 of 689 by trust here, #504 by citations
• Computer Graphics and Computer-Aided Design — 30 citations into it; #246 of 1,584 by trust here, #388 by citations
• Model Architectures — 29 citations into it
• Aerospace Engineering — 25 citations into it
• Geology — 18 citations into it

Whom Ayan Sinha trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Diederik P. Kingma
5. Ross B. Girshick
6. Yann LeCun
7. Yoshua Bengio
8. Ilya Sutskever
9. Karen Simonyan
10. Christian Szegedy

Who trusts Ayan Sinha overall

1. Zhiqin Chen
2. Matan Atzmon
3. Nitika Verma
4. Yaron Lipman
5. Min Liu
6. Thibault Groueix
7. Adrien Poulenard
8. Andrea Tagliasacchi
9. Haggai Maron
10. Zhangjie Cao

Papers from Ayan Sinha's perspective

Ordered by how strongly the researchers Ayan Sinha 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. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
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

• Deep Learning 3D Shape Surfaces Using Geometry Images (2016) — 336 citations
• Atlas: End-to-End 3D Scene Reconstruction from Posed Images (2020) — 349 citations
• Gradient Adversarial Training of Neural Networks (2018) — 41 citations
• Imaging through glass diffusers using densely connected convolutional networks (2017) — 345 citations
• Deep Learning 3D Shapes Using Alt-az Anisotropic 2-Sphere Convolution (2018) — 45 citations
• SurfNet: Generating 3D Shape Surfaces Using Deep Residual Networks (2017) — 187 citations
• Lensless computational imaging through deep learning (2017) — 588 citations