Zhaoyang Zeng

Computer Vision and Pattern Recognition · 2020–2023

A researcher in the Science corpus: 4 papers; trusts 423 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 146 citations into it; #6,293 of 21,575 by trust here, #3,445 by citations
• Artificial Intelligence — 120 citations into it; #9,217 of 35,345 by trust here, #4,559 by citations
• Multimodal Learning — 78 citations into it; #352 of 1,211 by trust here, #308 by citations
• Natural Language Processing — 35 citations into it
• Model Architectures — 33 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Large Language Models — 11 citations into it
• Optimization & Training — 6 citations into it

Whom Zhaoyang Zeng trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Ross B. Girshick
4. Alex Krizhevsky
5. Yoshua Bengio
6. Shaoqing Ren
7. Diederik P. Kingma
8. Ilya Sutskever
9. Yann LeCun
10. Tsung-Yi Lin

Who trusts Zhaoyang Zeng overall

1. Zhe Gan
2. Jianfeng Wang
3. Yupan Huang
4. Linjie Li
5. Zi-Yi Dou
6. Zhengyuan Yang
7. Jaemin Cho
8. Xiaowei Hu
9. Yan Zeng
10. Hongwei Xue

Papers from Zhaoyang Zeng's perspective

Ordered by how strongly the researchers Zhaoyang Zeng 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Pixel-BERT: Aligning Image Pixels with Text by Deep Multi-Modal Transformers (2020) — 475 citations
• Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection (2023) — 4,547 citations
• Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning (2021) — 313 citations
• CLIP4Caption ++: Multi-CLIP for Video Caption (2021) — 8 citations