Bo Zhang

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 11 papers; trusts 927 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 434 citations into it; #14,322 of 21,575 by trust here, #3,525 by citations
• Artificial Intelligence — 235 citations into it
• Generative Models — 214 citations into it
• Multimodal Learning — 70 citations into it
• Computer Graphics and Computer-Aided Design — 61 citations into it; #1,575 of 1,584 by trust here, #196 by citations
• Model Architectures — 43 citations into it
• Optimization & Training — 36 citations into it
• Statistical and Nonlinear Physics — 25 citations into it

Whom Bo Zhang trusts overall

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

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

Who trusts Bo Zhang overall

1. Tengfei Wang
2. Juwon Seo
3. Peng Wang
4. Lvmin Zhang
5. Agrim Gupta
6. Ting Zhang
7. Yichun Shi
8. Jingwen Kang
9. Xiaoyu Li

Papers from Bo Zhang's perspective

Ordered by how strongly the researchers Bo 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Vector Quantized Diffusion Model for Text-to-Image Synthesis (2021) — 1,090 citations
• Pretraining is All You Need for Image-to-Image Translation (2022) — 216 citations
• DeepSeek-VL: Towards Real-World Vision-Language Understanding (2024) — 847 citations
• Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior (2023) — 420 citations
• Paint by Example: Exemplar-based Image Editing with Diffusion Models (2022) — 643 citations
• StyleSwin: Transformer-based GAN for High-resolution Image Generation (2021) — 311 citations
• RODIN: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion (2022) — 393 citations
• Cross-Domain Correspondence Learning for Exemplar-Based Image Translation (2020) — 266 citations
• Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (2021) — 592 citations
• DeepSeek LLM: Scaling Open-Source Language Models with Longtermism (2024) — 805 citations
• Deep Sketch-Guided Cartoon Video Inbetweening (2021) — 34 citations