Agrim Gupta

Computer Vision and Pattern Recognition · with Fei-Fei · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 437 researchers and is trusted by 173 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 77 citations into it; #2,791 of 21,575 by trust here, #3,713 by citations
• Artificial Intelligence — 57 citations into it; #5,421 of 35,345 by trust here, #4,923 by citations
• Generative Models — 30 citations into it; #416 of 1,956 by trust here, #620 by citations
• Graph Learning — 12 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Model Architectures — 11 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Optimization & Training — 8 citations into it

Whom Agrim Gupta trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Yann LeCun
6. Kaiming He
7. Ilya Sutskever
8. Alex Graves
9. Jimmy Ba
10. Max Welling

Who trusts Agrim Gupta overall

1. Tianfu Wu
2. Boris Ivanovic
3. Karttikeya Mangalam
4. Nicholas Rhinehart
5. Chen Sun
6. Ye Yuan
7. Yu Kong
8. Kris M. Kitani
9. Bo Zhao
10. Tobias Hinz

Papers from Agrim Gupta's perspective

Ordered by how strongly the researchers Agrim Gupta 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. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
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

• Image Generation from Scene Graphs (2018) — 933 citations
• Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks (2018) — 2,420 citations
• Embodied intelligence via learning and evolution (2021) — 436 citations