Image data를 바탕으로 모델을 구현하고 정리합니다.
베이스가 되는 모델부터 최신 모델까지 구조를 공부하는 것을 목표로 합니다. (2022년도 업로드 예정)
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- Very Deep Convolutional Networks for Large-Scale Image Recognition. Karen Simonyan, Andrew Zisserman
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- Going Deeper with Convolutions Christian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke, Andrew Rabinovich
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- Deep Residual Learning for Image Recognition Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
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- Densely Connected Convolutional Networks Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
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- Xception: Deep Learning with Depthwise Separable Convolutions François Chollet
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- Aggregated Residual Transformations for Deep Neural Networks Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, Kaiming He
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- Hu, Jie and Shen, Li and Albanie, Samuel and Sun, Gang and Wu, Enhua
| ConvNet | Dataset | Published In |
|---|---|---|
| VGGNet | STL10 | ICLR2015 |
| GoogleNet | STL10 | CVPR2015 |
| ResNet | STL10 | CVPR2015 |
| DenseNet | - | ECCV2017 |
| ResNeXt | CIFAR10 | CVPR2017 |
| SEResNet | - | CVPR2018 |
Table of Contents
- CodeLab
- Computer Vision
- Natural Language Processing
- Tabular Data
- Time-Series
- Reinforcement Learning
- Audio Data
- Multi-modality
- Extra
- Pytorch Accelerator
Classification
- Model Soup [Jaehyuk Heo]
- Point cloud classification with PointNet [Hyeongwon Kang]
- Involutional neural networks [Subin Kim]
- Image classification with Vision Transformer [Jaehyuk Heo]
- Video Classification with Transformers + Video Vision Transformer [Hyeongwon Kang]
Self-Supervised Learning
- Semi-supervised image classification using contrastive pretraining with SimCLR [Subin Kim]
- Self-supervised contrastive learning with SimSiam [Jaehyuk Heo]
- Supervised Contrastive Learning [Subin Kim]
Image Denoising
- Convolutional autoencoder for image denoising [Jeongseob Kim]
Segmentation
- Point cloud segmentation with PointNet [Hyeongwon Kang]
- Image segmentation with a U-Net-like architecture [Jeongseob Kim]
Object Detection
- Object Detection with RetinaNet [Jaehyuk Heo]
Knowledge Distillation
- Knowledge Distillation [Jaehyuk Heo]
Retrieval
- Metric learning for image similarity search [Jaehyuk Heo]
- Image similarity estimation using a Siamese Network with a triplet loss [Yonggi Jeong]
OCR
- OCR model for reading Captchas [Subin Kim]
Augmentation
- RandAugment for Image Classification for Improved Robustness [Yonggi Jeong]
- CutMix data augmentation for image classification [Jaehyuk Heo]
Clustering
- Semantic Image Clustering [Yonggi Jeong]
Depth Estimation
- Monocular depth estimation [Hyeongwon Kang]
Attribution Methods
- Grad-CAM class activation visualization [Jaehyuk Heo]
- Model interpretability with Integrated Gradients [Jaehyuk Heo]
- Visualizing what convnets learn [Jaehyuk Heo]
Optimizer
- Gradient Centralization for Better Training Performance [Jaehyuk Heo]
Adepter
- Finetuning ViT with LoRA [Jaehyuk Heo]
Generative Models
- Variational AutoEncoder [Jaehyuk Heo]
- DCGAN to generate face images [Hyeongwon Kang]
- Neural style transfer [Subin Kim]
- Deep Dream [Jaehyuk Heo]
- Conditional GAN [Yonggi Jeong]
- CycleGAN [Yonggi Jeong]
- PixelCNN [Jeongseob Kim]
- Density estimation using Real NVP [Jeongseob Kim]
- Non-linear Independent Component Estimation (NICE) [Jeongseob Kim]
- Diffusion generative model(Tutorials) [Jeongseob Kim]
- Diffusion generative model(Examples - Swiss-roll, MNIST, F-MNIST, CELEBA) [Jeongseob Kim]
- Score based generative model(Tutorials) [Jeongseob Kim]
Adversarial Attacks
- Fast Gradient Sign Method [Jaehyuk Heo]
- Projected Gradient Descent [Jaehyuk Heo]
Adversarial Detection
- Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain [Jaehyuk Heo]
Anomaly Detection
- PatchCore: Towards Total Recall in Industrial Anomaly Detection [Jaehyuk Heo]
- MemSeg: A semi-supervised method for image surface defect detection using differences and commonalities [Jaehyuk Heo]
Classification
- Text classification with Switch Transformer [Subin Kim]
- Text classification with Transformer [Yookyung Kho]
- Bidirectional LSTM on IMDB [Jeongseob Kim]
Generation
- Text generation with a miniature GPT [Subin Kim]
- Sequence to sequence learning for performing number addition [Yookyung Kho]
- Character-level recurrent sequence-to-sequence model [Jeongseob Kim]
- English-to-Spanish translation with a sequence-to-sequence Transformer [Yookyung Kho]
Question Answering
- Question Answering with Hugging Face Transformers [Yookyung Kho]
- Text Extraction with BERT [Jaehyuk Heo]
Pretrained Language Model
- End-to-end Masked Language Modeling with BERT [Subin Kim]
Named Entity Recognition
- Named Entity Recognition using Transformers [Subin Kim]
Natural Language Inference
- Semantic Similarity with BERT [Jaehyuk Heo]
Table MRC
- Table Pre-training with TapasForMaskedLM [Yookyung Kho]
Tutorial
- TorchText introduction [Jeongseob Kim]
Classification
- Classification with Gated Residual and Variable Selection Networks [Hyeongwon Kang]
- Structured data learning with TabTransformer [Hyeongwon Kang]
Recommendation
- Collaborative Filtering for Movie Recommendations [Hyeongwon Kang]
- A Transformer-based recommendation system [Hyeongwon Kang]
Anomaly Detection
Anomaly Detection
- Timeseries anomaly detection using an Autoencoder [Hyeongwon Kang]
Classification
- Timeseries classification with a Transformer model [Hyeongwon Kang]
Forecasting
- Timeseries forecasting for weather prediction [Hyeongwon Kang]
- Actor Critic Method [Hyeongwon Kang]
- Deep Deterministic Policy Gradient (DDPG) [Hyeongwon Kang]
- Deep Q-Learning for Atari Breakout [Hyeongwon Kang]
- Proximal Policy Optimization [Hyeongwon Kang]
Recognition
- Speaker Recognition [Subin Kim]
Vision-Langauge
- Multimodal entailment [Yookyung Kho]
- Natural language image search with a Dual Encoder [Subin Kim]
- Distributions_TFP_Pyro [Jeongseob Kim]
- Huggingface Accelerator [Jaehyuk Heo]
- Automatic Mixed Precision [Jaehyuk Heo]
- Gradient Accumulation [Jaehyuk Heo]
- Distributed Data Parallel [Jaehyuk Heo]