Georg Volk

Computer Vision and Pattern Recognition · 2018–2019

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 — 27 citations into it
• Evaluation & Benchmarks — 13 citations into it
• Aerospace Engineering — 6 citations into it

Whom Georg Volk trusts overall

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

1. Joseph Redmon
2. Kaiming He
3. Ross B. Girshick
4. Mark Everingham
5. Shaoqing Ren
6. Andreas Geiger
7. Geoffrey E. Hinton
8. Alex Krizhevsky
9. Tsung-Yi Lin
10. Andrew Zisserman

Who trusts Georg Volk overall

1. Claudio Michaelis

Papers from Georg Volk's perspective

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

Their papers

• Towards Robust CNN-based Object Detection through Augmentation with Synthetic Rain Variations (2019) — 91 citations
• Simulating Photo-realistic Snow and Fog on Existing Images for Enhanced CNN Training and Evaluation (2019) — 52 citations
• Rendering Physically Correct Raindrops on Windshields for Robustness Verification of Camera-based Object Recognition (2018) — 23 citations