Zilong Huang

Computer Vision and Pattern Recognition · with Wang · 2018–2022

A researcher in the Science corpus: 8 papers; trusts 1,075 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 299 citations into it; #5,107 of 21,575 by trust here, #2,536 by citations
• Artificial Intelligence — 154 citations into it
• Model Architectures — 71 citations into it
• Evaluation & Benchmarks — 23 citations into it
• Control and Systems Engineering — 20 citations into it
• Efficiency & Compression — 19 citations into it
• Optimization & Training — 18 citations into it
• Generative Models — 17 citations into it

Whom Zilong Huang 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. Karen Simonyan
6. Yoshua Bengio
7. Diederik P. Kingma
8. Yann LeCun
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Zilong Huang overall

1. Yuhui Yuan
2. Bowen Cheng
3. Qibin Hou
4. Arthur Douillard
5. Chang-Bin Zhang
6. Jun Fu
7. Kai Han
8. Huiyu Wang
9. Meng-Hao Guo
10. Jingdong Wang

Papers from Zilong Huang's perspective

Ordered by how strongly the researchers Zilong Huang 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. Attention is All you Need (Neural Information Processing Systems)
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• CCNet: Criss-Cross Attention for Semantic Segmentation (2018) — 3,049 citations
• Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer (2021) — 214 citations
• SPGNet: Semantic Prediction Guidance for Scene Parsing (2019) — 117 citations
• Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (2018) — 589 citations
• TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation (2022) — 301 citations
• A PyTorch Semantic Segmentation Toolbox (2018)
• Executing your Commands via Motion Diffusion in Latent Space (2022) — 696 citations
• Half-Real Half-Fake Distillation for Class-Incremental Semantic Segmentation (2021) — 13 citations