Guoliang Kang

Computer Vision and Pattern Recognition · 2017–2023

A researcher in the Science corpus: 9 papers; trusts 1,179 researchers and is trusted by 430 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 291 citations into it; #2,046 of 21,575 by trust here, #1,755 by citations
• Artificial Intelligence — 223 citations into it; #15,008 of 35,345 by trust here, #6,720 by citations
• Representation & Self-Supervised Learning — 65 citations into it; #2,053 of 3,145 by trust here, #1,741 by citations
• Model Architectures — 39 citations into it
• Meta & Continual Learning — 32 citations into it
• Efficiency & Compression — 20 citations into it; #1,175 of 1,264 by trust here, #731 by citations
• Optimization & Training — 19 citations into it
• Evaluation & Benchmarks — 18 citations into it

Whom Guoliang Kang trusts overall

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

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

Who trusts Guoliang Kang overall

1. Garrett Wilson
2. Umberto Michieli
3. Mohammad Rostami
4. Yi Yang
5. Liang Zheng
6. Zhun Zhong
7. Kaiyang Zhou
8. Xuanyi Dong
9. Qiming Zhang
10. Fuzhen Zhuang

Papers from Guoliang Kang's perspective

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

• Random Erasing Data Augmentation (2017) — 4,240 citations
• Contrastive Adaptation Network for Unsupervised Domain Adaptation (2019) — 991 citations
• Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks (2018) — 1,076 citations
• Image-Image Domain Adaptation with Preserved Self-Similarity and Domain-Dissimilarity for Person Re-identification (2017) — 970 citations
• Self-produced Guidance for Weakly-supervised Object Localization (2018) — 267 citations
• Few-Shot Segmentation via Cycle-Consistent Transformer (2021) — 271 citations
• SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model (2023) — 207 citations
• Domain Consensus Clustering for Universal Domain Adaptation (2021) — 151 citations
• Multi-Interest Network with Dynamic Routing for Recommendation at Tmall (2019) — 508 citations