Seung-Wook Kim
Computer Vision and Pattern Recognition · with Ko · 2018–2019
A researcher in the Science corpus: 3 papers; trusts 564 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 92 citations into it
- Artificial Intelligence — 25 citations into it
- Generative Models — 24 citations into it
- Optimization & Training — 10 citations into it
- Computer Graphics and Computer-Aided Design — 9 citations into it
- Model Architectures — 9 citations into it
- Media Technology — 8 citations into it
Whom Seung-Wook Kim trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ross B. Girshick
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yoshua Bengio
- Karen Simonyan
- Christian Szegedy
- Shaoqing Ren
- Yann LeCun
- Tsung-Yi Lin
Who trusts Seung-Wook Kim overall
Papers from Seung-Wook Kim's perspective
Ordered by how strongly the researchers Seung-Wook Kim 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
- 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
- Going deeper with convolutions
Their papers
- PEPSI : Fast Image Inpainting With Parallel Decoding Network (2019) — 123 citations
- Parallel Feature Pyramid Network for Object Detection (2018) — 286 citations
- PEPSI++: Fast and Lightweight Network for Image Inpainting (2019) — 109 citations