Tianhao Zhang

Computer Vision and Pattern Recognition · with Li · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 556 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 84 citations into it; #14,023 of 21,575 by trust here, #16,367 by citations
• Generative Models — 52 citations into it; #1,341 of 1,956 by trust here, #1,651 by citations
• Artificial Intelligence — 21 citations into it
• Computer Graphics and Computer-Aided Design — 10 citations into it; #1,012 of 1,584 by trust here, #1,116 by citations
• Multimodal Learning — 10 citations into it
• Evaluation & Benchmarks — 9 citations into it
• Media Technology — 5 citations into it
• Model Architectures — 5 citations into it

Whom Tianhao Zhang trusts overall

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

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

Who trusts Tianhao Zhang overall

1. Utkarsh Ojha
2. Zhen Zhu
3. D. Epstein
4. Sheng-Yu Wang
5. Jörn-Henrik Jacobsen
6. Vadim Sushko
7. Chuqiao Li

Papers from Tianhao Zhang's perspective

Ordered by how strongly the researchers Tianhao Zhang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
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

• Diverse Image Synthesis From Semantic Layouts via Conditional IMLE (2018) — 107 citations
• Text as Neural Operator:Image Manipulation by Text Instruction (2020) — 41 citations
• A Study of Robustness of Neural Nets Using Approximate Feature Collisions (2018)