Kaican Li
Computer Vision and Pattern Recognition · 2018–2020
A researcher in the Science corpus: 2 papers; trusts 313 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 61 citations into it
- Artificial Intelligence — 40 citations into it
- Representation & Self-Supervised Learning — 11 citations into it
- Model Architectures — 10 citations into it
- Optimization & Training — 7 citations into it
- Generative Models — 5 citations into it
Whom Kaican Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Diederik P. Kingma
- Alex Krizhevsky
- Geoffrey E. Hinton
- Karen Simonyan
- Ross B. Girshick
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Andrew Zisserman
Who trusts Kaican Li overall
Papers from Kaican Li's perspective
Ordered by how strongly the researchers Kaican Li 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
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Guided Collaborative Training for Pixel-wise Semi-Supervised Learning (2020) — 296 citations
- Referring Image Segmentation via Recurrent Refinement Networks (2018) — 294 citations