Timo Milbich

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 5 papers; trusts 810 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 226 citations into it; #18,505 of 21,575 by trust here, #12,419 by citations
• Artificial Intelligence — 127 citations into it
• Generative Models — 96 citations into it; #1,756 of 1,956 by trust here, #1,577 by citations
• Representation & Self-Supervised Learning — 51 citations into it
• Optimization & Training — 29 citations into it
• Signal Processing — 22 citations into it
• Evaluation & Benchmarks — 21 citations into it
• Model Architectures — 17 citations into it

Whom Timo Milbich trusts overall

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

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

Who trusts Timo Milbich overall

1. Andreas Blattmann
2. Jinbo Xing

Papers from Timo Milbich's perspective

Ordered by how strongly the researchers Timo Milbich 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

• Revisiting Training Strategies and Generalization Performance in Deep Metric Learning (2020) — 191 citations
• Stochastic Image-to-Video Synthesis using cINNs (2021) — 67 citations
• iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis (2021) — 52 citations
• Behavior-Driven Synthesis of Human Dynamics (2021) — 16 citations
• Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning (2021) — 25 citations