Haowen Deng
Computer Vision and Pattern Recognition · 2018
A researcher in the Science corpus: 3 papers; trusts 297 researchers and is trusted by 38 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 65 citations into it
- Computational Mechanics — 43 citations into it; #1,010 of 10,001 by trust here, #2,509 by citations
- Aerospace Engineering — 36 citations into it; #474 of 6,421 by trust here, #1,815 by citations
- Geology — 32 citations into it; #68 of 687 by trust here, #263 by citations
- 3D Vision & Pose — 16 citations into it
- Artificial Intelligence — 14 citations into it
- Representation & Self-Supervised Learning — 10 citations into it
- Generative Models — 8 citations into it
Whom Haowen Deng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- David G. Lowe
- L. V. D. van der Maaten
- Kaiming He
- Radu Bogdan Rusu
- Jianxiong Xiao
- Yann LeCun
- Andrew E. Johnson
- Ilya Sutskever
Who trusts Haowen Deng overall
- Christopher Bongsoo Choy
- Xiaoshui Huang
- Zan Gojcic
- Xuyang Bai
- Weixin Lu
- Fu Li
- Sheng Ao
- Zi Jian Yew
- Guofeng Mei
- Vladlen Koltun
Papers from Haowen Deng's perspective
Ordered by how strongly the researchers Haowen Deng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- PPFNet: Global Context Aware Local Features for Robust 3D Point Matching (2018) — 639 citations
- 3D Point Capsule Networks (2018) — 365 citations
- PPF-FoldNet: Unsupervised Learning of Rotation Invariant 3D Local Descriptors (2018) — 435 citations