Ravi Garg

Computer Vision and Pattern Recognition · 2013–2018

A researcher in the Science corpus: 3 papers; trusts 287 researchers and is trusted by 60 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 72 citations into it; #3,885 of 21,575 by trust here, #4,834 by citations
• Aerospace Engineering — 18 citations into it; #3,045 of 6,421 by trust here, #2,245 by citations
• Artificial Intelligence — 12 citations into it
• 3D Vision & Pose — 10 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Media Technology — 10 citations into it; #616 of 3,621 by trust here, #392 by citations
• Computational Mechanics — 6 citations into it

Whom Ravi Garg trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. David G. Lowe
4. Yann LeCun
5. Kaiming He
6. Diederik P. Kingma
7. Ross B. Girshick
8. Ilya Sutskever
9. Yoshua Bengio
10. Andrea Vedaldi

Who trusts Ravi Garg overall

1. Clément Godard
2. Jamie Watson
3. Oisin Mac Aodha
4. Alex Kendall
5. Yuliang Zou
6. Gabriel J. Brostow
7. Sudeep Pillai
8. Reza Mahjourian
9. Amir Atapour-Abarghouei
10. Zhichao Yin

Papers from Ravi Garg's perspective

Ordered by how strongly the researchers Ravi Garg 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. Attention is All you Need (Neural Information Processing Systems)
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

• Unsupervised CNN for Single View Depth Estimation: Geometry to the Rescue (2016) — 1,652 citations
• Dense Variational Reconstruction of Non-rigid Surfaces from Monocular Video (2013) — 244 citations
• Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction (2018) — 694 citations