Jianzhuang Liu
Computer Vision and Pattern Recognition · 2010–2023
A researcher in the Science corpus: 10 papers; trusts 1,064 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 371 citations into it; #10,052 of 21,575 by trust here, #6,542 by citations
- Artificial Intelligence — 189 citations into it
- Model Architectures — 70 citations into it
- Generative Models — 60 citations into it
- Media Technology — 59 citations into it; #1,571 of 3,621 by trust here, #910 by citations
- Representation & Self-Supervised Learning — 35 citations into it
- Evaluation & Benchmarks — 25 citations into it
- Optimization & Training — 19 citations into it
Whom Jianzhuang Liu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Ross B. Girshick
- Yoshua Bengio
- Yann LeCun
- Diederik P. Kingma
- Karen Simonyan
- Ilya Sutskever
- Andrew Zisserman
Who trusts Jianzhuang Liu overall
Papers from Jianzhuang Liu's perspective
Ordered by how strongly the researchers Jianzhuang Liu 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Uformer: A General U-Shaped Transformer for Image Restoration (2021) — 2,238 citations
- Prompt Distribution Learning (2022) — 353 citations
- Implicit Diffusion Models for Continuous Super-Resolution (2023) — 383 citations
- Anti-Retroactive Interference for Lifelong Learning (2022) — 30 citations
- TRAR: Routing the Attention Spans in Transformer for Visual Question Answering (2021) — 132 citations
- Context-Transformer: Tackling Object Confusion for Few-Shot Detection (2020) — 93 citations
- Unsupervised Image Super-Resolution with an Indirect Supervised Path (2019) — 49 citations
- Multinomial Distribution Learning for Effective Neural Architecture Search (2019) — 100 citations
- Gabor Convolutional Networks (2017) — 395 citations
- Local Derivative Pattern Versus Local Binary Pattern: Face Recognition With High-Order Local Pattern Descriptor (2010) — 1,104 citations