Christoph Schnörr
Computer Vision and Pattern Recognition · 2001–2014
A researcher in the Science corpus: 7 papers; trusts 20 researchers and is trusted by 292 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 50 citations into it; #2,318 of 21,575 by trust here, #4,750 by citations
- Artificial Intelligence — 16 citations into it; #12,182 of 35,345 by trust here, #15,542 by citations
- Probabilistic & Bayesian Methods — 10 citations into it
- Computational Mechanics — 6 citations into it
Whom Christoph Schnörr trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Robert Tibshirani
- Jason Aaron Edward Weston
- Joachim Weickert
- Luis Álvarez
- Alan L. Yuille
- Olivier Chapelle
- Olvi L. Mangasarian
- Kristin P. Bennett
- Paul S. Bradley
- Geoffrey E. Hinton
Who trusts Christoph Schnörr overall
- Thomas Brox
- Daniel Cremers
- Qinghua Hu
- Deqing Sun
- Massimo Minervini
- Ce Liu
- Joachim Weickert
- Bharath K. Sriperumbudur
- Tianshu Liu
- Hanno Scharr
Papers from Christoph Schnörr's perspective
Ordered by how strongly the researchers Christoph Schnörr trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Universität Des Saarlandes Fachrichtung 6.1 – Mathematik Lucas/kanade Meets Horn/schunck: Combining Local and Global Optic Flow Methods Lucas/kanade Meets Horn/schunck: Combining Local and Global Optic Flow Methods
- Natural Image Statistics for Natural Image Segmentation (2003) — 550 citations
- A Comparative Study of Modern Inference Techniques for Structured Discrete Energy Minimization Problems (2014) — 190 citations
- A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion (2001) — 344 citations
- Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint (2001) — 321 citations
- Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional (2002) — 390 citations
- Combined SVM-Based Feature Selection and Classification (2005) — 279 citations