Gang Zhang

Computer Vision and Pattern Recognition · with Li · 2020–2023

A researcher in the Science corpus: 3 papers; trusts 83 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 72 citations into it
• Artificial Intelligence — 52 citations into it

Whom Gang Zhang trusts overall

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

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

Papers from Gang Zhang's perspective

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

Their papers

• AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results (2020) — 43 citations
• 1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask (2020) — 19 citations
• A Unified Continual Learning Framework with General Parameter-Efficient Tuning (2023) — 161 citations