Xirong Li
Computer Vision and Pattern Recognition · with Dong · 2012–2019
A researcher in the Science corpus: 9 papers; trusts 1,035 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 185 citations into it; #10,092 of 21,575 by trust here, #7,092 by citations
- Artificial Intelligence — 146 citations into it; #29,519 of 35,345 by trust here, #10,207 by citations
- Natural Language Processing — 68 citations into it; #3,797 of 5,688 by trust here, #2,407 by citations
- Multimodal Learning — 67 citations into it; #741 of 1,211 by trust here, #756 by citations
- Evaluation & Benchmarks — 34 citations into it
- Information Systems — 25 citations into it
- Model Architectures — 20 citations into it
- Representation & Self-Supervised Learning — 20 citations into it
Whom Xirong Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Ilya Sutskever
- Ross B. Girshick
- Chih-Jen Lin
- Oriol Vinyals
Who trusts Xirong Li overall
- Xiaojie Wang
- Zechao Li
- Niluthpol Chowdhury Mithun
- Yue Gao
- Zhe Chen
- Haoyang Huang
- Andrea Burns
- Cees G. M. Snoek
- Emanuele Bugliarello
- Rui Zhang
Papers from Xirong Li's perspective
Ordered by how strongly the researchers Xirong Li trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Dual Encoding for Zero-Example Video Retrieval (2018) — 299 citations
- COCO-CN for Cross-Lingual Image Tagging, Captioning, and Retrieval (2018) — 186 citations
- Fluency-Guided Cross-Lingual Image Captioning (2017) — 108 citations
- Predicting Visual Features From Text for Image and Video Caption Retrieval (2017) — 243 citations
- Deep Text Classification Can be Fooled (2017) — 452 citations
- Content-based visual search learned from social media (2012) — 309 citations
- Mining Dual Emotion for Fake News Detection (2019) — 348 citations
- Word2VisualVec: Image and Video to Sentence Matching by Visual Feature Prediction (2016) — 61 citations
- Classifying tag relevance with relevant positive and negative examples (2013) — 44 citations