Seungjae Shin
Computer Vision and Pattern Recognition · 2021
A researcher in the Science corpus: 2 papers; trusts 276 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 80 citations into it
- Artificial Intelligence — 44 citations into it
- Generative Models — 35 citations into it
- Efficiency & Compression — 16 citations into it
- Evaluation & Benchmarks — 10 citations into it
- Statistical and Nonlinear Physics — 10 citations into it
- Probabilistic & Bayesian Methods — 9 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
Whom Seungjae Shin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
- Ross B. Girshick
- Max Welling
- Yang Song
Who trusts Seungjae Shin overall
Papers from Seungjae Shin's perspective
Ordered by how strongly the researchers Seungjae Shin 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
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Refine Myself by Teaching Myself: Feature Refinement via Self-Knowledge Distillation (2021) — 180 citations
- Score Matching Model for Unbounded Data Score (2021) — 32 citations