Yuhua Chen

Computer Vision and Pattern Recognition · with Gool · 2017–2020

A researcher in the Science corpus: 6 papers; trusts 1,377 researchers and is trusted by 144 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 277 citations into it; #2,897 of 21,575 by trust here, #3,378 by citations
• Artificial Intelligence — 163 citations into it; #4,518 of 35,345 by trust here, #4,923 by citations
• Representation & Self-Supervised Learning — 61 citations into it; #2,781 of 3,145 by trust here, #2,217 by citations
• Generative Models — 28 citations into it
• Evaluation & Benchmarks — 25 citations into it
• Cancer Research — 18 citations into it
• Radiology, Nuclear Medicine and Imaging — 18 citations into it; #2,030 of 3,265 by trust here, #934 by citations
• Model Architectures — 16 citations into it

Whom Yuhua Chen trusts overall

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

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

Who trusts Yuhua Chen overall

1. Dengxin Dai
2. Lukas Hoyer
3. Luc Van Gool
4. Wen Li
5. Garrett Wilson
6. Yahao Liu
7. Yanchao Yang
8. Jinhong Deng
9. Yang Zou
10. Matteo Biasetton

Papers from Yuhua Chen's perspective

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

Their papers

• Domain Adaptive Faster R-CNN for Object Detection in the Wild (2018) — 1,565 citations
• Video Object Segmentation without Temporal Information (2017) — 358 citations
• DLOW: Domain Flow for Adaptation and Generalization (2018) — 400 citations
• ROAD: Reality Oriented Adaptation for Semantic Segmentation of Urban Scenes (2017) — 316 citations
• Learning Semantic Segmentation From Synthetic Data: A Geometrically Guided Input-Output Adaptation Approach (2018) — 276 citations
• Unbiased Mean Teacher for Cross-domain Object Detection (2020) — 400 citations