Feifan Lv
Computer Vision and Pattern Recognition · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 427 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 87 citations into it
- Media Technology — 42 citations into it
- Atomic and Molecular Physics, and Optics — 9 citations into it
- Evaluation & Benchmarks — 8 citations into it
- Generative Models — 8 citations into it
- Optimization & Training — 6 citations into it
- Model Architectures — 5 citations into it
Whom Feifan Lv trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Karen Simonyan
- Zhou Wang
- Geoffrey E. Hinton
- Andrew Zisserman
- Alex Krizhevsky
- Hamid R. Sheikh
- Sergey Ioffe
- Ross B. Girshick
Who trusts Feifan Lv overall
- Chongyi Li
- Christos Sakaridis
- Yufei Wang
- Wen-Bin Wu
- Jiaying Liu
- Hao Bian
- Zhenqi Fu
- Wenhan Yang
- Chunle Guo
- Dengxin Dai
Papers from Feifan Lv's perspective
Ordered by how strongly the researchers Feifan Lv 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (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
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Attention Guided Low-Light Image Enhancement with a Large Scale Low-Light Simulation Dataset (2019) — 330 citations
- MBLLEN: Low-Light Image/Video Enhancement Using CNNs (2018) — 794 citations