Nanxuan Zhao

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 4 papers; trusts 664 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 176 citations into it
• Artificial Intelligence — 68 citations into it
• Computer Graphics and Computer-Aided Design — 47 citations into it
• Representation & Self-Supervised Learning — 47 citations into it
• 3D Vision & Pose — 16 citations into it
• Generative Models — 15 citations into it
• Evaluation & Benchmarks — 11 citations into it
• Aerospace Engineering — 10 citations into it

Whom Nanxuan Zhao trusts overall

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

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

Who trusts Nanxuan Zhao overall

1. Linus Ericsson
2. Wenke Huang
3. Jie Gui
4. Dapeng Hu
5. Chen Wei
6. Josip Djolonga
7. Mang Ye
8. Henry Gouk
9. Yifan Zhang
10. Qizhengqiu Lu

Papers from Nanxuan Zhao's perspective

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

Their papers

• Distilling Localization for Self-Supervised Representation Learning (2020) — 59 citations
• What makes instance discrimination good for transfer learning? (2020) — 183 citations
• GS-LRM: Large Reconstruction Model for 3D Gaussian Splatting (2024) — 348 citations
• BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-scale Scene Rendering (2021) — 323 citations