Xudong Lin
Computer Vision and Pattern Recognition · with Wang · 2019–2022
A researcher in the Science corpus: 7 papers; trusts 887 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 342 citations into it; #17,081 of 21,575 by trust here, #8,722 by citations
- Artificial Intelligence — 259 citations into it; #27,930 of 35,345 by trust here, #14,438 by citations
- Multimodal Learning — 189 citations into it
- Natural Language Processing — 76 citations into it
- Evaluation & Benchmarks — 53 citations into it
- Representation & Self-Supervised Learning — 52 citations into it
- Model Architectures — 43 citations into it; #1,814 of 2,278 by trust here, #2,192 by citations
- Large Language Models — 35 citations into it
Whom Xudong Lin trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Ross B. Girshick
- Diederik P. Kingma
- Yann LeCun
- Andrew Zisserman
- Ilya Sutskever
- Karen Simonyan
Who trusts Xudong Lin overall
Papers from Xudong Lin's perspective
Ordered by how strongly the researchers Xudong Lin 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)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- 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
- Going deeper with convolutions
Their papers
- All in One: Exploring Unified Video-Language Pre-Training (2022) — 254 citations
- VX2TEXT: End-to-End Learning of Video-Based Text Generation From Multimodal Inputs (2021) — 78 citations
- Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners (2022) — 171 citations
- Object-aware Video-language Pre-training for Retrieval (2021) — 90 citations
- Context-Gated Convolution (2019) — 73 citations
- MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding (2021) — 37 citations
- Video-Text Pre-training with Learned Regions (2021) — 30 citations