Omkar M. Parkhi
Computer Vision and Pattern Recognition · 1969–2021
A researcher in the Science corpus: 7 papers; trusts 1,144 researchers and is trusted by 3,604 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 159 citations into it; #569 of 21,575 by trust here, #1,335 by citations
- Artificial Intelligence — 37 citations into it
- Signal Processing — 23 citations into it; #1,543 of 7,572 by trust here, #823 by citations
- Evaluation & Benchmarks — 17 citations into it; #924 of 3,147 by trust here, #1,018 by citations
- Media Technology — 11 citations into it
- Aerospace Engineering — 10 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Model Architectures — 9 citations into it
Whom Omkar M. Parkhi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Andrew Zisserman
- Karen Simonyan
- Andrea Vedaldi
- Kaiming He
- Alex Krizhevsky
- Josef Sivic
- Geoffrey E. Hinton
- Ross B. Girshick
- David G. Lowe
- Yann LeCun
Who trusts Omkar M. Parkhi overall
- Andrew Zisserman
- Arsha Nagrani
- Andrea Vedaldi
- Jitendra Malik
- Xiaogang Wang
- Trevor Darrell
- Rahaf Aljundi
- Dacheng Tao
- Bharath Hariharan
- Ning Zhang
Papers from Omkar M. Parkhi's perspective
Ordered by how strongly the researchers Omkar M. Parkhi trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Deep Face Recognition (2015) — 5,654 citations
- The truth about cats and dogs (2011) — 142 citations
- VGGFace2: A Dataset for Recognising Faces across Pose and Age (2017) — 3,096 citations
- Fisher Vector Faces in the Wild (2013) — 487 citations
- It ’ s in the bag : Stronger supervision for automated face labelling (2015)
- Pointly-Supervised Instance Segmentation (2021) — 149 citations
- Care of aged doctors (1969)