Feng Liu
Computer Vision and Pattern Recognition · with Hospedales · 2016–2017
A researcher in the Science corpus: 4 papers; trusts 354 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 88 citations into it; #6,948 of 21,575 by trust here, #6,542 by citations
- Artificial Intelligence — 58 citations into it; #13,707 of 35,345 by trust here, #11,490 by citations
- Natural Language Processing — 24 citations into it
- Model Architectures — 18 citations into it
- Reinforcement Learning — 8 citations into it
Whom Feng Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Oriol Vinyals
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Christian Szegedy
- Diederik P. Kingma
- Alex Graves
- Kaiming He
Who trusts Feng Liu overall
- Ayan Kumar Bhunia
- Aneeshan Sain
- Yi-Zhe Song
- Pinaki Nath Chowdhury
- Tao A. Xiang
- Jifei Song
- Yongxin Yang
- Kaiyue Pang
- Timothy M. Hospedales
- Li Zhang
Papers from Feng Liu's perspective
Ordered by how strongly the researchers Feng Liu trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Sketch Me That Shoe (2016) — 481 citations
- Actor-Critic Sequence Training for Image Captioning (2017) — 116 citations
- Sketch-a-Net: A Deep Neural Network that Beats Humans (2016) — 341 citations
- Semantic Regularisation for Recurrent Image Annotation (2016) — 111 citations