Jonas Unger

Computer Vision and Pattern Recognition · 2005–2020

A researcher in the Science corpus: 5 papers; trusts 480 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 89 citations into it; #6,613 of 21,575 by trust here, #9,435 by citations
• Artificial Intelligence — 53 citations into it
• Evaluation & Benchmarks — 19 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Safety, Robustness & Interpretability — 15 citations into it
• Aerospace Engineering — 9 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 7 citations into it

Whom Jonas Unger trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Diederik P. Kingma
6. Christian Szegedy
7. Shaoqing Ren
8. Ross B. Girshick
9. Karen Simonyan
10. Yann LeCun

Who trusts Jonas Unger overall

1. Sergey I. Nikolenko
2. Myeongjin Kim
3. Fredrik K. Gustafsson
4. Sumanth Chennupati
5. Samin Rahman Khan
6. Fei Pan
7. Hyeran Byun

Papers from Jonas Unger's perspective

Ordered by how strongly the researchers Jonas Unger 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. ImageNet Large Scale Visual Recognition Challenge
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Going deeper with convolutions

Their papers

• Procedural Modeling and Physically Based Rendering for Synthetic Data Generation in Automotive Applications (2017) — 85 citations
• HDR image reconstruction from a single exposure using deep CNNs (2017) — 626 citations
• Synscapes: A Photorealistic Synthetic Dataset for Street Scene Parsing (2018) — 233 citations
• Performance relighting and reflectance transformation with time-multiplexed illumination (2005) — 321 citations
• Measuring Domain Shift for Deep Learning in Histopathology (2020) — 282 citations