Sanskar Agrawal

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 144 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it
• Generative Models — 13 citations into it

Whom Sanskar Agrawal trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Yoshua Bengio
5. Diederik P. Kingma
6. Alexei A. Efros
7. Sepp Hochreiter
8. Karen Simonyan
9. Yann LeCun
10. Ross B. Girshick

Papers from Sanskar Agrawal's perspective

Ordered by how strongly the researchers Sanskar Agrawal 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. GENERATIVE ADVERSARIAL NETS
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Prior Guided GAN Based Semantic Inpainting (2020) — 101 citations