Jianfeng Dong
Computer Vision and Pattern Recognition · 2016–2018
A researcher in the Science corpus: 5 papers; trusts 862 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 129 citations into it; #10,761 of 21,575 by trust here, #7,852 by citations
- Artificial Intelligence — 95 citations into it; #21,564 of 35,345 by trust here, #19,439 by citations
- Multimodal Learning — 72 citations into it; #526 of 1,211 by trust here, #766 by citations
- Natural Language Processing — 51 citations into it; #4,733 of 5,688 by trust here, #5,296 by citations
- Evaluation & Benchmarks — 18 citations into it
- Model Architectures — 15 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
- Optimization & Training — 8 citations into it
Whom Jianfeng Dong trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yoshua Bengio
- Diederik P. Kingma
- Tomas Mikolov
- Ilya Sutskever
- Ross B. Girshick
- Yann LeCun
- Oriol Vinyals
Who trusts Jianfeng Dong overall
- Niluthpol Chowdhury Mithun
- Xirong Li
- Andy Zeng
- Antoine Miech
- Shizhe Chen
- Chaoxi Xu
- Han Fang
- Po-Yao (Bernie) Huang
- Jean-Baptiste Alayrac
- Yiwei Ma
Papers from Jianfeng Dong's perspective
Ordered by how strongly the researchers Jianfeng Dong 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)
- 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
- Exploring Human-like Attention Supervision in Visual Question Answering (2017) — 115 citations
- Fluency-Guided Cross-Lingual Image Captioning (2017) — 108 citations
- Predicting Visual Features From Text for Image and Video Caption Retrieval (2017) — 243 citations
- Word2VisualVec: Image and Video to Sentence Matching by Visual Feature Prediction (2016) — 61 citations