Cheng Chi
Computer Vision and Pattern Recognition · with Liu · 2019–2020
A researcher in the Science corpus: 3 papers; trusts 723 researchers and is trusted by 16 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 193 citations into it; #7,677 of 21,575 by trust here, #5,422 by citations
- Artificial Intelligence — 54 citations into it
- Model Architectures — 13 citations into it
- Aerospace Engineering — 11 citations into it
- Radiology, Nuclear Medicine and Imaging — 6 citations into it
Whom Cheng Chi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Ross B. Girshick
- Kaiming He
- Tsung-Yi Lin
- Alex Krizhevsky
- Geoffrey E. Hinton
- Jifeng Dai
- Shaoqing Ren
- Jia Deng
- Yann LeCun
- Yoshua Bengio
Who trusts Cheng Chi overall
- Zhiqing Sun
- Ze Liu
- Jianwei Yang
- Xiyang Dai
- Chien-Yao Wang
- Wenhai Wang
- Xiang-Yang Li
- Alexey Bochkovskiy
- Zheng Zhang
- Shengcao Cao
Papers from Cheng Chi's perspective
Ordered by how strongly the researchers Cheng Chi 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)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection (2019) — 2,144 citations
- Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study (2019) — 337 citations
- RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder (2020) — 73 citations