논문 읽기
1.[논문 읽기] DEPLOT: 그래프를 표로 변환하기
📃 논문 링크DEPLOT: One-shot visual language reasoning by plot-to-table translation주제: 그래프와 차트를 이미지처럼 인식하여 표 형태의 자연어로 풀어내는 모델(Plot-to-Table Translation)인
2.[논문 읽기] Transformer: Attention Is All You Need(2017)
분류: NLP저자: Google paper: Attention Is All You Need키워드: Transformer, Attention \*논문에 언급되지 않은 내용이 포함되어 있을 수 있습니다. 이는 보다 쉬운 이해를 위해서 포함되었습니다. 기존의 RNN이나 CN
3.[논문 읽기] AlexNet: ImageNet Classification with Deep Convolutional Neural Networks(2012)
분류: Vision Model저자: Alex Krizhevsky, IIya Sutskerver, Geoffrey E.Hinton소속: University of Torontopaper: ImageNet Classification with Deep Convolutional
4.[논문 읽기] R-CNN: Rich feature hierarchies for accurate object detection and sementic segmentation(2014)
분류: Object Detection저자: Ross Girshick, ,Jeff Donahue, Trevor Darrell, Jitendra Malik소속: UC Berkeleypaper: Rich feature hierarchies for accurate object
5.[논문 읽기] Word2Vec: Efficient Estimation of Word Representations in Vector Space(2013)
* 분류: Language Model > * 저자: Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean > * 소속: Google > * paper: Efficient Estimation of Word Representation
6.[논문 읽기] Seq2Seq: Sequence to Sequence Learning with Neural Networks(2014)
분류: Language Model저자: IIya Sutskever, Oriol Vinyals, Quoc V.Le소속: Googlepaper: Sequence to Sequence Learning with Neural Networks키워드: Seq2Seq, Reverse
7.[논문 읽기] GAN: Generative Adversarial Nets(2014)
분류: Image Generative Model저자: Ian j.Goodfellow, Jean Pouget-Abadie, …소속: University of Montrealpaper: Generative Adversarial Nets키워드: GAN, Generative
8.[논문 읽기] Knowledge Distillation: Distilling the Knowledge in a Neural Network(2015)
분류: ETC저자: Geoffrey Hinton, Oriol Vinyals, Jeff Dean 소속: Google paper: Distilling the Knowledge in a Neural Network키워드: knowledge distillation, model
9.[논문 읽기] Inception: Going deeper with convolutions(2014)
분류: Vision Model저자: Christian Szegedy, Wei Liu, Yangqing Jia, ...소속: Google, University of Nort Carolina, University of Michigan paper: Goint deeper w
10.[논문 읽기] VGGNet: Very Deep Convolutional Networks for Large-Scale Image Recognition(2015)
* 분류: Vision Model > * 저자: Karen Simonyan, Adrew Zisserman ... > * 소속: University of Oxford > * paper: Very Deep Convolutional Networks for Large-Scal
11.[논문 읽기] Explainable Recommendation: A Survey and New Perspectives(2020)
분류: XAI, Recommendation System저자: Yongfeng Zhang, Xu Chen소속: Rutgers University (Zhang), University of Science and Technology of China (Chen)paper: ht
12.[논문 읽기] Let Them Talk: Audio-Driven Multi-Person Conversational Video Generation(2025)
분류: Video Generation, Multi-modal저자: Zhe Kong, Feng Gao, Yong Zhang†, Zhuoliang Kang, Xiaoming Wei, Xunliang Cai, Guanying Chen, Wenhan Luo† 소속: Shenz