Yuan-fang Wang

Computer Vision and Pattern Recognition · 2004–2019

A researcher in the Science corpus: 6 papers; trusts 644 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 178 citations into it; #6,856 of 21,575 by trust here, #3,538 by citations
• Artificial Intelligence — 123 citations into it; #27,354 of 35,345 by trust here, #5,720 by citations
• Multimodal Learning — 65 citations into it; #725 of 1,211 by trust here, #373 by citations
• Natural Language Processing — 65 citations into it
• Reinforcement Learning — 33 citations into it; #1,427 of 2,242 by trust here, #673 by citations
• Evaluation & Benchmarks — 29 citations into it
• Model Architectures — 26 citations into it
• Optimization & Training — 11 citations into it

Whom Yuan-fang Wang trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Yoshua Bengio
6. Ilya Sutskever
7. Matthew D. Zeiler
8. Karen Simonyan
9. Yann LeCun
10. Sepp Hochreiter

Who trusts Yuan-fang Wang overall

1. Xin Eric Wang
2. Jie Lei
3. Aditya Mogadala
4. Jiawei Wu

Papers from Yuan-fang Wang's perspective

Ordered by how strongly the researchers Yuan-fang Wang 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. Attention is All you Need (Neural Information Processing Systems)
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

• Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language Navigation (2018) — 642 citations
• VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research (2019) — 718 citations
• Video Captioning via Hierarchical Reinforcement Learning (2017) — 254 citations
• MAN: Moment Alignment Network for Natural Language Moment Retrieval via Iterative Graph Adjustment (2018) — 344 citations
• Watch, Listen, and Describe: Globally and Locally Aligned Cross-Modal Attentions for Video Captioning (2018) — 80 citations
• Adaptive stream resource management using Kalman Filters (2004) — 383 citations