Zheng Zhu
Computer Vision and Pattern Recognition · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · 2018–2021
A researcher in the Science corpus: 8 papers; trusts 1,111 researchers and is trusted by 158 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 302 citations into it; #2,806 of 21,575 by trust here, #2,902 by citations
- Artificial Intelligence — 122 citations into it
- Model Architectures — 53 citations into it
- Evaluation & Benchmarks — 31 citations into it
- Aerospace Engineering — 23 citations into it; #2,699 of 6,421 by trust here, #3,072 by citations
- Optimization & Training — 21 citations into it
- Representation & Self-Supervised Learning — 21 citations into it
- Efficiency & Compression — 10 citations into it
Whom Zheng Zhu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Ross B. Girshick
- Geoffrey E. Hinton
- Ilya Sutskever
- Yoshua Bengio
- Karen Simonyan
- Diederik P. Kingma
- Yann LeCun
- Shaoqing Ren
Who trusts Zheng Zhu overall
- Martin Danelljan
- Goutam Bhat
- Dongyan Guo
- Qiang Wang
- Zhipeng Zhang
- Heng Fan
- Houwen Peng
- Rohit Girdhar
- Bo Li
- Paul Voigtlaender
Papers from Zheng Zhu's perspective
Ordered by how strongly the researchers Zheng Zhu 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)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- High Performance Visual Tracking with Siamese Region Proposal Network (2018) — 2,552 citations
- Attention-Guided Unified Network for Panoptic Segmentation (2018) — 293 citations
- Distractor-aware Siamese Networks for Visual Object Tracking (2018) — 1,303 citations
- DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting (2021) — 830 citations
- BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View (2021) — 1,076 citations
- Global Filter Networks for Image Classification (2021) — 726 citations
- WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition (2021) — 355 citations
- An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes (2018) — 28 citations