Dejing Xu

Computer Vision and Pattern Recognition · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 525 researchers and is trusted by 74 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 150 citations into it; #3,677 of 21,575 by trust here, #3,680 by citations
• Artificial Intelligence — 107 citations into it; #14,452 of 35,345 by trust here, #6,103 by citations
• Multimodal Learning — 43 citations into it
• Natural Language Processing — 26 citations into it
• Representation & Self-Supervised Learning — 19 citations into it; #3,073 of 3,145 by trust here, #1,885 by citations
• Evaluation & Benchmarks — 18 citations into it
• Question Answering & Reading Comprehension — 18 citations into it; #108 of 335 by trust here, #31 by citations
• Model Architectures — 16 citations into it

Whom Dejing Xu trusts overall

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

1. Karen Simonyan
2. Kaiming He
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Andrew Zisserman
7. Yoshua Bengio
8. Ilya Sutskever
9. Ross B. Girshick
10. Yann LeCun

Who trusts Dejing Xu overall

1. Paul Hongsuck Seo
2. Junbin Xiao
3. Chenyou Fan
4. Rowan Zellers
5. Cordelia Schmid
6. Yueting Zhuang
7. Zhou Zhao
8. Devshree Patel
9. Arsha Nagrani
10. Antoine Yang

Papers from Dejing Xu's perspective

Ordered by how strongly the researchers Dejing Xu 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. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Video Question Answering via Gradually Refined Attention over Appearance and Motion (2017) — 817 citations
• ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering (2019) — 754 citations
• Self-Supervised Spatiotemporal Learning via Video Clip Order Prediction (2019) — 481 citations
• Multichannel Attention Refinement for Video Question Answering (2020) — 31 citations