Yuejian Fang
Computer Vision and Pattern Recognition · 2019–2021
A researcher in the Science corpus: 2 papers; trusts 236 researchers and is trusted by 95 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 72 citations into it; #3,268 of 21,575 by trust here, #3,239 by citations
- Artificial Intelligence — 43 citations into it; #6,625 of 35,345 by trust here, #5,221 by citations
- Multimodal Learning — 31 citations into it; #260 of 1,211 by trust here, #347 by citations
- Natural Language Processing — 20 citations into it
- Model Architectures — 8 citations into it
Whom Yuejian Fang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Karen Simonyan
- Yoshua Bengio
- Ilya Sutskever
- Alec Radford
- Ross B. Girshick
- Yann LeCun
Who trusts Yuejian Fang overall
- Zhe Gan
- Linjie Li
- Yen-Chun Chen
- Pengchuan Zhang
- Xiaowei Hu
- Jianfeng Wang
- Zhicheng Huang
- Ronghang Hu
- Junyang Lin
- Jiasen Lu
Papers from Yuejian Fang's perspective
Ordered by how strongly the researchers Yuejian Fang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training (2019) — 975 citations
- NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion (2021) — 369 citations