Bowen Zhang

Computer Vision and Pattern Recognition · with Wang · 2016–2021

A researcher in the Science corpus: 3 papers; trusts 559 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 97 citations into it; #6,661 of 21,575 by trust here, #6,737 by citations
• Artificial Intelligence — 59 citations into it; #26,445 of 35,345 by trust here, #14,718 by citations
• Multimodal Learning — 18 citations into it; #912 of 1,211 by trust here, #795 by citations
• Model Architectures — 14 citations into it
• Natural Language Processing — 14 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Representation & Self-Supervised Learning — 7 citations into it
• Endocrinology, Diabetes and Metabolism — 5 citations into it

Whom Bowen Zhang trusts overall

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

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

Who trusts Bowen Zhang overall

1. Limin Wang
2. Jianwei Yang
3. Tianhao Li
4. Mohammadreza Zolfaghari
5. Han Fang
6. Zuxuan Wu
7. Valentin Gabeur
8. Gul Varol
9. Victor Escorcia
10. Jie Lei

Papers from Bowen Zhang's perspective

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

Their papers

• Real-Time Action Recognition with Enhanced Motion Vector CNNs (2016) — 439 citations
• Cross-Modal and Hierarchical Modeling of Video and Text (2018) — 208 citations
• Co-training Transformer with Videos and Images Improves Action Recognition (2021) — 63 citations