Chaoning Zhang

Computer Vision and Pattern Recognition · 2020–2023

A researcher in the Science corpus: 7 papers; trusts 747 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 267 citations into it
• Artificial Intelligence — 229 citations into it
• Generative Models — 85 citations into it
• Representation & Self-Supervised Learning — 69 citations into it
• Multimodal Learning — 35 citations into it
• Model Architectures — 32 citations into it
• Safety, Robustness & Interpretability — 31 citations into it
• Computer Graphics and Computer-Aided Design — 20 citations into it

Whom Chaoning Zhang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Diederik P. Kingma
6. Yoshua Bengio
7. Ilya Sutskever
8. Yann LeCun
9. Christian Szegedy
10. Karen Simonyan

Who trusts Chaoning Zhang overall

1. Siyu Wang
2. Ao Wang
3. Naoki Yokoyama
4. Yunyang Xiong
5. Roya Firoozi

Papers from Chaoning Zhang's perspective

Ordered by how strongly the researchers Chaoning Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Faster Segment Anything: Towards Lightweight SAM for Mobile Applications (2023) — 649 citations
• Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo (2022) — 74 citations
• Text-to-image Diffusion Models in Generative AI: A Survey (2023) — 439 citations
• A Survey On Universal Adversarial Attack (2021) — 115 citations
• A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI (2023) — 118 citations
• A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond (2022) — 102 citations
• ResNet or DenseNet? Introducing Dense Shortcuts to ResNet (2020) — 153 citations