Xiuye Gu

Computer Vision and Pattern Recognition · with Cui · 2021–2022

A researcher in the Science corpus: 5 papers; trusts 1,140 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 204 citations into it; #5,059 of 21,575 by trust here, #4,690 by citations
• Artificial Intelligence — 147 citations into it; #21,071 of 35,345 by trust here, #8,525 by citations
• Multimodal Learning — 51 citations into it; #628 of 1,211 by trust here, #471 by citations
• Representation & Self-Supervised Learning — 39 citations into it
• Evaluation & Benchmarks — 31 citations into it
• Radiology, Nuclear Medicine and Imaging — 18 citations into it
• Model Architectures — 16 citations into it
• Meta & Continual Learning — 13 citations into it

Whom Xiuye Gu trusts overall

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

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

Who trusts Xiuye Gu overall

1. Zheng Ding
2. Rohit Girdhar
3. Jiarui Xu
4. Timo Lüddecke
5. Justin Kerr
6. Jingyi Zhang
7. Jianwei Yang
8. Xingyi Zhou
9. Zhuowen Tu
10. Yuhang Zang

Papers from Xiuye Gu's perspective

Ordered by how strongly the researchers Xiuye Gu 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. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
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

• Open-vocabulary Object Detection via Vision and Language Knowledge Distillation (2021) — 1,353 citations
• Open-Vocabulary Image Segmentation (2021) — 97 citations
• Zero-Shot Detection via Vision and Language Knowledge Distillation (2021) — 90 citations
• F-VLM: Open-Vocabulary Object Detection upon Frozen Vision and Language Models (2022) — 199 citations
• Scaling Open-Vocabulary Image Segmentation with Image-Level Labels (2021) — 614 citations