Xu Yang
Computer Vision and Pattern Recognition · with Cai · 2018–2020
A researcher in the Science corpus: 3 papers; trusts 963 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 140 citations into it; #7,709 of 21,575 by trust here, #7,852 by citations
- Artificial Intelligence — 115 citations into it; #28,811 of 35,345 by trust here, #27,551 by citations
- Multimodal Learning — 64 citations into it; #406 of 1,211 by trust here, #642 by citations
- Natural Language Processing — 57 citations into it; #2,802 of 5,688 by trust here, #2,695 by citations
- Evaluation & Benchmarks — 33 citations into it
- Model Architectures — 15 citations into it
- Graph Learning — 8 citations into it
- Optimization & Training — 8 citations into it
Whom Xu Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Ilya Sutskever
- Ross B. Girshick
- Shaoqing Ren
- Jimmy Ba
- Yann LeCun
Who trusts Xu Yang overall
- Marcella Cornia
- Matteo Stefanini
- Ruotian Luo
- Hanwang Zhang
- Lorenzo Baraldi
- Ron Mokady
- Feihong Shen
- Rita Cucchiara
- Xinting Hu
- Danna Gurari
Papers from Xu Yang's perspective
Ordered by how strongly the researchers Xu Yang 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- 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
- Auto-Encoding Scene Graphs for Image Captioning (2018) — 801 citations
- Deconfounded Image Captioning: A Causal Retrospect (2020) — 161 citations
- Learning to Collocate Neural Modules for Image Captioning (2019) — 84 citations