Qi She

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 9 papers; trusts 777 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 283 citations into it; #16,968 of 21,575 by trust here, #7,657 by citations
• Artificial Intelligence — 180 citations into it
• Generative Models — 78 citations into it
• Model Architectures — 53 citations into it
• Meta & Continual Learning — 33 citations into it
• Evaluation & Benchmarks — 32 citations into it
• Representation & Self-Supervised Learning — 25 citations into it
• Optimization & Training — 21 citations into it

Whom Qi She trusts overall

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

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

Who trusts Qi She overall

1. Jungseok Hong
2. Simon Vandenhende
3. Ximeng Sun

Papers from Qi She's perspective

Ordered by how strongly the researchers Qi She trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Involution: Inverting the Inherence of Convolution for Visual Recognition (2021) — 392 citations
• Avalanche: an End-to-End Library for Continual Learning (2021) — 219 citations
• NDDR-CNN: Layerwise Feature Fusing in Multi-Task CNNs by Neural Discriminative Dimensionality Reduction (2018) — 306 citations
• CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition (2020) — 20 citations
• CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions (2020) — 54 citations
• Challenges in Task Incremental Learning for Assistive Robotics (2020) — 37 citations
• Generative Adversarial Networks: A Survey and Taxonomy (2019) — 93 citations
• Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for Lifelong SLAM (2019) — 193 citations
• Synthetic-Neuroscore: Using a neuro-AI interface for evaluating generative adversarial networks (2019) — 13 citations