Tomasz Trzcinski

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

A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 35 citations into it
• Artificial Intelligence — 33 citations into it
• 3D Vision & Pose — 13 citations into it
• Generative Models — 8 citations into it

Whom Tomasz Trzcinski trusts overall

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

1. Snehashish Chakraverty
2. Deepti Moyi Sahoo
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Kaiming He
6. Diederik P. Kingma
7. Yoshua Bengio
8. Zhiqin Chen
9. Ilya Sutskever
10. Yann LeCun

Papers from Tomasz Trzcinski's perspective

Ordered by how strongly the researchers Tomasz Trzcinski 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. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Continual Learning with Guarantees via Weight Interval Constraints (2022) — 13 citations
• HyperCube: Implicit Field Representations of Voxelized 3D Models (2021) — 5 citations