Punarjay Chakravarty

Computer Vision and Pattern Recognition · 2016–2020

A researcher in the Science corpus: 4 papers; trusts 546 researchers and is trusted by 196 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 77 citations into it; #2,668 of 21,575 by trust here, #3,313 by citations
• Artificial Intelligence — 44 citations into it; #2,816 of 35,345 by trust here, #4,466 by citations
• Automotive Engineering — 17 citations into it
• Representation & Self-Supervised Learning — 17 citations into it; #442 of 3,145 by trust here, #640 by citations
• Signal Processing — 10 citations into it; #3,369 of 7,572 by trust here, #4,051 by citations
• Evaluation & Benchmarks — 9 citations into it
• Model Architectures — 8 citations into it

Whom Punarjay Chakravarty trusts overall

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

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

Who trusts Punarjay Chakravarty overall

1. Rahaf Aljundi
2. Joon Son Chung
3. Andrew Zisserman
4. Arsha Nagrani
5. Marc Masana
6. Arslan Chaudhry
7. Gyuhak Kim
8. Tinne Tuytelaars
9. Marcus Rohrbach
10. Marc'Aurelio Ranzato

Papers from Punarjay Chakravarty's perspective

Ordered by how strongly the researchers Punarjay Chakravarty 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. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• Expert Gate: Lifelong Learning with a Network of Experts (2016) — 771 citations
• Trajectron++: Dynamically-Feasible Trajectory Forecasting with Heterogeneous Data (2020) — 1,349 citations
• Cross-Modal Supervision for Learning Active Speaker Detection in Video (2016) — 78 citations
• Who's that Actor? Automatic Labelling of Actors in TV Series Starting from IMDB Images (2016) — 13 citations