Bryan A. Plummer

Computer Vision and Pattern Recognition · 2015–2022

A researcher in the Science corpus: 5 papers; trusts 810 researchers and is trusted by 467 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 166 citations into it; #1,961 of 21,575 by trust here, #2,456 by citations
• Artificial Intelligence — 114 citations into it; #5,334 of 35,345 by trust here, #3,609 by citations
• Multimodal Learning — 77 citations into it; #200 of 1,211 by trust here, #238 by citations
• Natural Language Processing — 58 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Evaluation & Benchmarks — 17 citations into it
• Model Architectures — 14 citations into it
• Signal Processing — 11 citations into it

Whom Bryan A. Plummer trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Geoffrey E. Hinton
4. David G. Lowe
5. Alex Krizhevsky
6. Yoshua Bengio
7. Karen Simonyan
8. Oriol Vinyals
9. Diederik P. Kingma
10. Ilya Sutskever

Who trusts Bryan A. Plummer overall

1. Zhengyuan Yang
2. Zhe Gan
3. Ronghang Hu
4. Liunian Harold Li
5. Marcus Rohrbach
6. Jiuxiang Gu
7. Yen-Chun Chen
8. Antoine Miech
9. Emiel van Miltenburg
10. Liwei Wang

Papers from Bryan A. Plummer's perspective

Ordered by how strongly the researchers Bryan A. Plummer trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions

Their papers

• Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models (2015) — 2,641 citations
• Enhancing Video Summarization via Vision-Language Embedding (2017) — 113 citations
• Multilevel Language and Vision Integration for Text-to-Clip Retrieval (2018) — 369 citations
• Learning to Scale Multilingual Representations for Vision-Language Tasks (2020) — 36 citations
• Interactive Mobile App Navigation with Uncertain or Under-specified Natural Language Commands (2022) — 10 citations