Marcus Lim
Computer Vision and Pattern Recognition · 2012
A researcher in the Science corpus: 2 papers; trusts 91 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 31 citations into it; #8,674 of 21,575 by trust here, #9,305 by citations
- Artificial Intelligence — 10 citations into it
- Aerospace Engineering — 8 citations into it; #2,947 of 6,421 by trust here, #2,580 by citations
- Control and Systems Engineering — 7 citations into it; #4,037 of 8,257 by trust here, #2,528 by citations
- Computational Mechanics — 6 citations into it
- 3D Vision & Pose — 5 citations into it; #469 of 689 by trust here, #584 by citations
Whom Marcus Lim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ashutosh Saxena
- Radford M. Neal
- Daphne Koller
- Yee Whye Teh
- B. Taskar
- Rob Fergus
- Geoffrey E. Hinton
- Jia Deng
- Li Fei-Fei
- Andrew Y. Ng
Who trusts Marcus Lim overall
- Hema Swetha Koppula
- Ashutosh Saxena
- Yun Jiang
- Rudhir Gupta
- Jaeyong Sung
- Abhishek Anand
- Ashesh Jain
- Roozbeh Mottaghi
- Oier Mees
- Thomas Whelan
Papers from Marcus Lim's perspective
Ordered by how strongly the researchers Marcus Lim 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- 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)
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Learning Object Arrangements in 3D Scenes using Human Context (2012) — 113 citations
- Learning to place new objects in a scene (2012) — 159 citations