Gaurav Sharma

Computer Vision and Pattern Recognition · with Sikka · 2012–2018

A researcher in the Science corpus: 4 papers; trusts 785 researchers and is trusted by 225 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 131 citations into it; #2,536 of 21,575 by trust here, #4,245 by citations
• Artificial Intelligence — 80 citations into it; #15,500 of 35,345 by trust here, #9,465 by citations
• Representation & Self-Supervised Learning — 25 citations into it; #1,742 of 3,145 by trust here, #1,338 by citations
• Natural Language Processing — 9 citations into it
• Biomedical Engineering — 6 citations into it
• Model Architectures — 5 citations into it

Whom Gaurav Sharma trusts overall

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

1. Andrew Zisserman
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Diederik P. Kingma
7. Yoshua Bengio
8. Manik Varma
9. Karen Simonyan
10. Cordelia Schmid

Who trusts Gaurav Sharma overall

1. Anne Humeau-Heurtier
2. Shafin Rahman
3. Mircea Cimpoi
4. Yongqin Xian
5. Karen Simonyan
6. Subhransu Maji
7. Andrea Vedaldi
8. Salman Hameed Khan
9. Pengkai Zhu
10. Iasonas Kokkinos

Papers from Gaurav Sharma's perspective

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

• Zero-Shot Object Detection (2018) — 418 citations
• Latent Embeddings for Zero-Shot Classification (2016) — 750 citations
• Local Higher-Order Statistics (LHS) for Texture Categorization and Facial Analysis (2012) — 142 citations
• AdaScan: Adaptive Scan Pooling in Deep Convolutional Neural Networks for Human Action Recognition in Videos (2016) — 159 citations