Guangchen Shi

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 130 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 48 citations into it
• Artificial Intelligence — 36 citations into it

Whom Guangchen Shi trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Ross B. Girshick
4. Alex Krizhevsky
5. Chi Zhang
6. Yoshua Bengio
7. Diederik P. Kingma
8. Yann LeCun
9. Tsung-Yi Lin
10. Ilya Sutskever

Papers from Guangchen Shi's perspective

Ordered by how strongly the researchers Guangchen Shi 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
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

• Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class Representation (2022) — 46 citations
• ARNet: Active-Reference Network for Few-Shot Image Semantic Segmentation (2021) — 7 citations