Nick Barnes
Computer Vision and Pattern Recognition · 2004–2023
A researcher in the Science corpus: 11 papers; trusts 1,677 researchers and is trusted by 38 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 463 citations into it; #4,524 of 21,575 by trust here, #5,890 by citations
- Artificial Intelligence — 402 citations into it; #10,887 of 35,345 by trust here, #14,181 by citations
- Natural Language Processing — 129 citations into it
- Media Technology — 111 citations into it; #663 of 3,621 by trust here, #1,550 by citations
- Evaluation & Benchmarks — 96 citations into it
- Model Architectures — 56 citations into it
- Computational Mechanics — 48 citations into it
- Efficiency & Compression — 36 citations into it
Whom Nick Barnes trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Diederik P. Kingma
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Yoshua Bengio
- Karen Simonyan
- Yann LeCun
- Ilya Sutskever
- Shaoqing Ren
Who trusts Nick Barnes overall
- Syed Waqas Zamir
- Salman Hameed Khan
- Aditya Arora
- Shafin Rahman
- Saeed Anwar
- Fahad Shahbaz Khan
- Munawar Hayat
- Yingying Zhu
- Chong Mou
- Andreas Møgelmose
Papers from Nick Barnes's perspective
Ordered by how strongly the researchers Nick Barnes 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)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Improved Visual-Semantic Alignment for Zero-Shot Object Detection (2020) — 124 citations
- Transductive Learning for Zero-Shot Object Detection (2019) — 84 citations
- A Deep Journey into Super-resolution (2019) — 489 citations
- Densely Residual Laplacian Super-Resolution (2019) — 281 citations
- A Comprehensive Overview of Large Language Models (2023) — 1,803 citations
- Simultaneously Localize, Segment and Rank the Camouflaged Objects (2021) — 555 citations
- UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders (2020) — 377 citations
- Any-Shot Object Detection (2020) — 19 citations
- Geometric Back-Projection Network for Point Cloud Classification (2019) — 295 citations
- Real Image Denoising With Feature Attention (2019) — 673 citations
- Fast shape-based road sign detection for a driver assistance system (2004) — 371 citations