Jian Zhang
Computer Vision and Pattern Recognition · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · 2014–2023
A researcher in the Science corpus: 5 papers; trusts 542 researchers and is trusted by 26 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 139 citations into it; #4,969 of 21,575 by trust here, #10,500 by citations
- Generative Models — 46 citations into it
- Artificial Intelligence — 45 citations into it
- Computational Mechanics — 45 citations into it; #1,370 of 10,001 by trust here, #3,275 by citations
- Signal Processing — 17 citations into it
- Media Technology — 16 citations into it
- Meta & Continual Learning — 16 citations into it
- Mathematical Physics — 13 citations into it
Whom Jian Zhang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Alex Krizhevsky
- Kaiming He
- Geoffrey E. Hinton
- Yann LeCun
- Yoshua Bengio
- Jimmy Ba
- Ilya Sutskever
- Gregory K. Wallace
- Karol Gregor
Who trusts Jian Zhang overall
- Zahra Kadkhodaie
- Chong Mou
- Wuzhen Shi
- Eero P. Simoncelli
- Kai Zhang
- Jun Shu
- Jinxi Xiang
- Qian Wang
- Zhonghao Zhang
- Feng Jiang
Papers from Jian Zhang's perspective
Ordered by how strongly the researchers Jian Zhang 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)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model (2022) — 767 citations
- ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing (2017) — 1,342 citations
- FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model (2023) — 344 citations
- R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental Learning (2022) — 102 citations
- Group-Based Sparse Representation for Image Restoration (2014) — 730 citations