Yana Hasson

Computer Vision and Pattern Recognition · with Laptev · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 353 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 127 citations into it; #20,994 of 21,575 by trust here, #8,831 by citations
• Control and Systems Engineering — 66 citations into it
• Human-Computer Interaction — 59 citations into it; #2,182 of 2,253 by trust here, #477 by citations
• 3D Vision & Pose — 39 citations into it; #687 of 689 by trust here, #354 by citations
• Computational Mechanics — 25 citations into it
• Evaluation & Benchmarks — 15 citations into it
• Artificial Intelligence — 14 citations into it
• Computer Graphics and Computer-Aided Design — 12 citations into it

Whom Yana Hasson trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Angjoo Kanazawa
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Ross B. Girshick
7. Jimmy Ba
8. Jitendra Malik
9. Yann LeCun
10. Yoshua Bengio

Who trusts Yana Hasson overall

1. Lingzhi Zhang
2. Omid Taheri
3. Yu-Wei Chao
4. Gyeongsik Moon
5. Zhe Cao
6. Dandan Shan
7. Supreeth Narasimhaswamy
8. Korrawe Karunratanakul
9. Zicong Fan
10. Taein Kwon

Papers from Yana Hasson's perspective

Ordered by how strongly the researchers Yana Hasson 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. 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. Attention is All you Need (Neural Information Processing Systems)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Learning Joint Reconstruction of Hands and Manipulated Objects (2019) — 658 citations
• Leveraging Photometric Consistency Over Time for Sparsely Supervised Hand-Object Reconstruction (2020) — 226 citations
• Towards Unconstrained Joint Hand-Object Reconstruction From RGB Videos (2021) — 84 citations