Xiaodi Hou
Computer Vision and Pattern Recognition · 2007–2018
A researcher in the Science corpus: 9 papers; trusts 727 researchers and is trusted by 1,113 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 177 citations into it; #1,264 of 21,575 by trust here, #1,399 by citations
- Artificial Intelligence — 92 citations into it; #11,866 of 35,345 by trust here, #4,627 by citations
- Representation & Self-Supervised Learning — 53 citations into it
- Evaluation & Benchmarks — 28 citations into it; #2,498 of 3,147 by trust here, #2,971 by citations
- Cognitive Neuroscience — 20 citations into it; #122 of 10,852 by trust here, #624 by citations
- Model Architectures — 17 citations into it
- Media Technology — 14 citations into it
- Safety, Robustness & Interpretability — 10 citations into it
Whom Xiaodi Hou trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Laurent Itti
- Christof Koch
- Neil D. B. Bruce
- David R. Martin
- Antonio Torralba
- Geoffrey E. Hinton
- Jitendra Malik
- Alex Krizhevsky
- Pablo Arbeláez
- Kaiming He
Who trusts Xiaodi Hou overall
- Wenguan Wang
- Ali Borji
- Ming-Ming Cheng
- Jianbing Shen
- Junwei Han
- Yin Li
- Huchuan Lu
- Haibin Ling
- Guanbin Li
- Huaizu Jiang
Papers from Xiaodi Hou's perspective
Ordered by how strongly the researchers Xiaodi Hou 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Revisiting Batch Normalization For Practical Domain Adaptation (2016) — 695 citations
- Understanding Convolution for Semantic Segmentation (2017) — 1,908 citations
- The Secrets of Salient Object Segmentation (2014) — 1,322 citations
- Saliency Detection: A Spectral Residual Approach (2007) — 3,643 citations
- Demystifying Neural Style Transfer (2017) — 566 citations
- Image Signature: Highlighting Sparse Salient Regions (2012) — 903 citations
- Boundary Detection Benchmarking: Beyond F-Measures (2013) — 52 citations
- Adaptive Batch Normalization for practical domain adaptation (2018) — 629 citations
- Dynamic visual attention: searching for coding length increments (2008) — 488 citations