Karan Sapra

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 416 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 86 citations into it; #10,783 of 21,575 by trust here, #9,187 by citations
• Artificial Intelligence — 68 citations into it; #17,448 of 35,345 by trust here, #17,776 by citations
• Optimization & Training — 17 citations into it
• Model Architectures — 13 citations into it; #1,271 of 2,278 by trust here, #1,726 by citations
• Representation & Self-Supervised Learning — 10 citations into it

Whom Karan Sapra trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Liang-Chieh Chen
5. Yann LeCun
6. Ross B. Girshick
7. Yoshua Bengio
8. Karen Simonyan
9. Diederik P. Kingma
10. Ilya Sutskever

Who trusts Karan Sapra overall

1. Lukas Hoyer
2. Xiangtai Li
3. Yuval Nirkin
4. Ximeng Sun
5. Zhe Chen
6. Huajun Liu
7. Anh-Quan Cao
8. Wenhai Wang
9. Shervin Minaee
10. Liang-Chieh Chen

Papers from Karan Sapra's perspective

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

Their papers

• Improving Semantic Segmentation via Video Propagation and Label Relaxation (2018) — 415 citations
• Hierarchical Multi-Scale Attention for Semantic Segmentation (2020) — 500 citations
• Personalized Federated Learning with First Order Model Optimization (2020) — 434 citations
• Partial Convolution based Padding (2018) — 101 citations