Chenchen Zhu
Computer Vision and Pattern Recognition · with Savvides · 2018–2022
A researcher in the Science corpus: 6 papers; trusts 876 researchers and is trusted by 31 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 214 citations into it; #5,410 of 21,575 by trust here, #2,381 by citations
- Artificial Intelligence — 126 citations into it; #11,185 of 35,345 by trust here, #3,279 by citations
- Model Architectures — 29 citations into it
- Evaluation & Benchmarks — 26 citations into it
- Optimization & Training — 13 citations into it
- Aerospace Engineering — 11 citations into it
- Efficiency & Compression — 7 citations into it
- Media Technology — 6 citations into it
Whom Chenchen Zhu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Ross B. Girshick
- Tsung-Yi Lin
- Geoffrey E. Hinton
- Alex Krizhevsky
- Shaoqing Ren
- Piotr Doll'ar
- Jia Deng
- Karen Simonyan
- David G. Lowe
Who trusts Chenchen Zhu overall
- Haoyang Zhang
- Xiang-Yang Li
- Chengjian Feng
- Xingyi Zhou
- Depu Meng
- Tao Kong
- Xiang Long
- Songtao Liu
- Zhi Tian
- Feras Dayoub
Papers from Chenchen Zhu's perspective
Ordered by how strongly the researchers Chenchen 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)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- MMDetection: Open MMLab Detection Toolbox and Benchmark (2019) — 3,471 citations
- Feature Selective Anchor-Free Module for Single-Shot Object Detection (2019) — 917 citations
- Bounding Box Regression With Uncertainty for Accurate Object Detection (2018) — 546 citations
- Soft Anchor-Point Object Detection (2019) — 162 citations
- Solving Missing-Annotation Object Detection with Background Recalibration Loss (2020) — 61 citations
- 3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding (2022) — 7 citations