Qing Li
Computer Vision and Pattern Recognition · with Luo · 2016–2018
A researcher in the Science corpus: 3 papers; trusts 410 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 96 citations into it; #13,682 of 21,575 by trust here, #4,865 by citations
- Artificial Intelligence — 59 citations into it; #21,909 of 35,345 by trust here, #6,664 by citations
- Multimodal Learning — 36 citations into it; #856 of 1,211 by trust here, #1,033 by citations
- Natural Language Processing — 22 citations into it
- Question Answering & Reading Comprehension — 13 citations into it; #195 of 335 by trust here, #243 by citations
- Optimization & Training — 5 citations into it
Whom Qing Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Karen Simonyan
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Andrew Zisserman
- Yann LeCun
- Ross B. Girshick
Who trusts Qing Li overall
- Sarah Wiegreffe
- Ana Marasovic
- Ben Zion Vatashsky
- Jue Wang
- Zhengyuan Yang
- Amanpreet Singh
- Mohammadreza Zolfaghari
- Shimon Ullman
- Jianfeng Wang
- Ali Furkan Biten
Papers from Qing Li's perspective
Ordered by how strongly the researchers Qing Li 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)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- VizWiz Grand Challenge: Answering Visual Questions from Blind People (2018) — 1,264 citations
- Action Recognition by Learning Deep Multi-Granular Spatio-Temporal Video Representation (2016) — 129 citations
- VQA-E: Explaining, Elaborating, and Enhancing Your Answers for Visual Questions (2018) — 123 citations