Dimosthenis Karatzas
Computer Vision and Pattern Recognition · 2013–2021
A researcher in the Science corpus: 13 papers; trusts 1,178 researchers and is trusted by 73 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 283 citations into it; #3,552 of 21,575 by trust here, #1,679 by citations
- Artificial Intelligence — 154 citations into it; #14,992 of 35,345 by trust here, #5,638 by citations
- Natural Language Processing — 82 citations into it
- Multimodal Learning — 75 citations into it; #1,053 of 1,211 by trust here, #766 by citations
- Evaluation & Benchmarks — 58 citations into it; #2,114 of 3,147 by trust here, #1,217 by citations
- Representation & Self-Supervised Learning — 32 citations into it; #2,691 of 3,145 by trust here, #2,094 by citations
- Media Technology — 25 citations into it
- Model Architectures — 21 citations into it
Whom Dimosthenis Karatzas trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Yoshua Bengio
- Diederik P. Kingma
- Yann LeCun
- Karen Simonyan
- Lukás Neumann
- Andrew Zisserman
Who trusts Dimosthenis Karatzas overall
- Minghui Liao
- Xiang Bai
- Pengyuan Lyu
- Cong Yao
- Baoguang Shi
- Xue Yang
- Chengquan Zhang
- Ali Furkan Biten
- Tong He
- Ronghang Hu
Papers from Dimosthenis Karatzas's perspective
Ordered by how strongly the researchers Dimosthenis Karatzas 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
- Long Short-Term Memory
- 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
- ICDAR 2013 Robust Reading Competition (2013) — 1,473 citations
- Scene Text Visual Question Answering (2019) — 512 citations
- ICDAR 2015 competition on Robust Reading (2015) — 1,578 citations
- Self-Supervised Learning of Visual Features through Embedding Images into Text Topic Spaces (2017) — 130 citations
- DocVQA: A Dataset for VQA on Document Images (2020) — 1,520 citations
- InfographicVQA (2021) — 506 citations
- Let there be a clock on the beach: Reducing Object Hallucination in Image Captioning (2021) — 98 citations
- ICDAR2019 Competition on Scanned Receipt OCR and Information Extraction (2019) — 431 citations
- ICDAR2017 Robust Reading Challenge on Multi-Lingual Scene Text Detection and Script Identification - RRC-MLT (2017) — 417 citations
- TextProposals: A text-specific selective search algorithm for word spotting in the wild (2016) — 113 citations
- Exploring Hate Speech Detection in Multimodal Publications (2019) — 308 citations
- Self-Supervised Learning from Web Data for Multimodal Retrieval (2019) — 27 citations
- Improving patch-based scene text script identification with ensembles of conjoined networks (2016) — 79 citations