Yi Jiang
Computer Vision and Pattern Recognition · arXiv.org · 2020–2024
A researcher in the Science corpus: 8 papers; trusts 891 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 357 citations into it; #12,854 of 21,575 by trust here, #4,865 by citations
- Artificial Intelligence — 203 citations into it
- Generative Models — 73 citations into it
- Large Language Models — 60 citations into it
- Model Architectures — 47 citations into it
- Optimization & Training — 18 citations into it
- Natural Language Processing — 17 citations into it
- Statistical and Nonlinear Physics — 17 citations into it
Whom Yi Jiang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Karen Simonyan
- Jia Deng
Who trusts Yi Jiang overall
- Jinkun Cao
- Pei Sun
- Fangao Zeng
- Enze Xie
- Yunhao Du
- Wenhai Wang
- Jianwei Yang
- Shenyuan Gao
- Xiangtai Li
- Jiannan Wu
Papers from Yi Jiang's perspective
Ordered by how strongly the researchers Yi Jiang 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Sparse R-CNN: End-to-End Object Detection with Learnable Proposals (2020) — 1,499 citations
- TransTrack: Multiple-Object Tracking with Transformer (2020) — 798 citations
- ByteTrack: Multi-Object Tracking by Associating Every Detection Box (2021) — 2,498 citations
- Language as Queries for Referring Video Object Segmentation (2022) — 263 citations
- DanceTrack: Multi-Object Tracking in Uniform Appearance and Diverse Motion (2021) — 422 citations
- Infinity∞: Scaling Bitwise AutoRegressive Modeling for High-Resolution Image Synthesis (2024) — 299 citations
- Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction (2024) — 1,081 citations
- Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation (2024) — 767 citations