Karthik Ramani

Computer Vision and Pattern Recognition · 2005–2022

A researcher in the Science corpus: 11 papers; trusts 770 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 187 citations into it; #5,653 of 21,575 by trust here, #6,426 by citations
• Computational Mechanics — 73 citations into it; #1,337 of 10,001 by trust here, #1,249 by citations
• Artificial Intelligence — 58 citations into it
• Biomedical Engineering — 44 citations into it
• Mechanical Engineering — 34 citations into it
• 3D Vision & Pose — 29 citations into it; #481 of 689 by trust here, #504 by citations
• Computer Graphics and Computer-Aided Design — 29 citations into it; #250 of 1,584 by trust here, #388 by citations
• Model Architectures — 28 citations into it

Whom Karthik Ramani 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. Karen Simonyan
6. Ross B. Girshick
7. Yann LeCun
8. Yoshua Bengio
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Karthik Ramani overall

1. Zhiqin Chen
2. Matan Atzmon
3. Min Liu
4. Nitika Verma
5. Ayan Sinha
6. Yaron Lipman
7. Adrien Poulenard
8. Zhizhong Han
9. Thibault Groueix
10. Zhangjie Cao

Papers from Karthik Ramani's perspective

Ordered by how strongly the researchers Karthik Ramani 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. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Deep Learning 3D Shape Surfaces Using Geometry Images (2016) — 336 citations
• Developing an engineering shape benchmark for CAD models (2006) — 313 citations
• 3D Object Classification via Spherical Projections (2017) — 74 citations
• First-Person View Hand Segmentation of Multi-Modal Hand Activity Video Dataset (2020) — 11 citations
• InfoGCN: Representation Learning for Human Skeleton-based Action Recognition (2022) — 334 citations
• ConvPDE-UQ: Convolutional neural networks with quantified uncertainty for heterogeneous elliptic partial differential equations on varied domains (2019) — 108 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
• The status, challenges, and future of additive manufacturing in engineering (2015) — 2,379 citations
• The evolution, challenges, and future of knowledge representation in product design systems (2013) — 696 citations
• Three-dimensional shape searching: state-of-the-art review and future trends (2005) — 549 citations