F. Richard Yu

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 85 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 48 citations into it
• Computational Mechanics — 19 citations into it
• Computer Graphics and Computer-Aided Design — 10 citations into it
• Control and Systems Engineering — 6 citations into it

Whom F. Richard Yu trusts overall

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

1. Michael J. Black
2. Thiemo Alldieck
3. Geoffrey E. Hinton
4. Kaiming He
5. Angjoo Kanazawa
6. Alex Krizhevsky
7. Diederik P. Kingma
8. William E. Lorensen
9. Ross B. Girshick
10. Liang-Chieh Chen

Papers from F. Richard Yu's perspective

Ordered by how strongly the researchers F. Richard Yu 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. Attention is All you Need (Neural Information Processing Systems)
6. Et al
7. GENERATIVE ADVERSARIAL NETS
8. Gradient-based learning applied to document recognition
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose (2021) — 311 citations