연도 | 논문 | 내용 |
---|---|---|
Vision | ||
2014 | VAE (Kingma and Welling) | [✓] Training on MNIST [✓] Visualizing Encoder output [✓] Visualizing Decoder output [✓] Reconstructing image |
2015 | CAM (Zhou et al.) | [✓] Applying GoogLeNet [✓] Generating 'Class Activatio Map' [✓] Generating bounding box |
2016 | Gatys et al. | [✓] Experimenting on input image size [✓] Experimenting on VGGNet-19 with Batch normalization [✓] Applying VGGNet-19 |
YOLO (Redmon et al.) | [✓] Model architecture [✓] Visualizing ground truth on grid [✓] Visualizing model output [✓] Visualizing class probability map [ㅤ] Loss function [ㅤ] Training on VOC 2012 |
|
DCGAN (Radford et al.) | [✓] Training on CelebA at 64 × 64 [✓] Sampling [✓] Interpolating in latent space [ㅤ] Training on CelebA at 32 × 32 |
|
Noroozi et al. | [✓] Model architecture [✓] Chromatic aberration [✓] Permutation set |
|
Zhang et al. | [✓] Visualizing empirical probability distribution [ㅤ] Model architecture [ㅤ] Loss function [ㅤ] Training |
|
2014 2017 |
Conditional GAN (Mirza et al.) WGAN-GP (Gulrajani et al.) |
[✓] Training on MNIST |
2016 2017 |
VQ-VAE (Oord et al.) PixelCNN (Oord et al.) |
[✓] Training on Fashion MNIST [✓] Training on CIFAR-10 [✓] Sampling |
2017 | Pix2Pix (Isola et al.) | [✓] Experimenting on image mean and std [✓] Experimenting on nn.InstanceNorm2d() [✓] Training on Google Maps [✓] Training on Facades [ㅤ] higher resolution input image |
CycleGAN (Zhu et al.) | [✓] Experimenting on random image pairing [✓] Experimenting on LSGANs [✓] Training on monet2photo [✓] Training on vangogh2photo [✓] Training on cezanne2photo [✓] Training on ukiyoe2photo [✓] Training on horse2zebra [✓] Training on summer2winter_yosemite |
|
2018 | PGGAN (Karras et al.) | [✓] Experimenting on image mean and std [✓] Training on CelebA-HQ at 512 × 512 [✓] Sampling |
DeepLabv3 (Chen et al.) | [✓] Training on VOC 2012 [✓] Predicting on VOC 2012 validation set [✓] Average mIoU [✓] Visualizing model output |
|
RotNet (Gidaris et al.) | [✓] Visualizing Attention map | |
StarGAN (Yunjey Choi et al.) | [✓] Model architecture | |
2020 | STEFANN (Roy et al.) | [✓] FANnet architecture [✓] Colornet architecture [✓] Training FANnet on Google Fonts [✓] Custom Google Fonts dataset [✓] Average SSIM [ㅤ] Training Colornet |
DDPM (Ho et al.) | [✓] Training on CelebA at 32 × 32 [✓] Training on CelebA at 64 × 64 [✓] Visualizing denoising process [✓] Sampling using linear interpolation [✓] Sampling using coarse-to-fine interpolation |
|
DDIM (Song et al.) | [✓] Normal sampling [✓] Sampling using spherical linear interpolation [✓] Sampling using grid interpolation [✓] Truncated normal |
|
ViT (Dosovitskiy et al.) | [✓] Training on CIFAR-10 [✓] Training on CIFAR-100 [✓] Visualizing Attention map using Attention Roll-out [✓] Visualizing position embedding similarity [✓] Interpolating position embedding [✓] CutOut [✓] CutMix [✓] Hide-and-Seek |
|
SimCLR (Chen et al.) | [✓] Normalized temperature-scaled cross entropy loss [✓] Data augmentation [✓] Pixel intensity histogram |
|
DETR (Carion et al.) | [✓] Model architecture [ㅤ] Bipartite matching & loss [ㅤ] Batch normalization freezing [ㅤ] Training on COCO 2017 |
|
2021 | Improved DDPM (Nichol and Dhariwal) | [✓] Cosine diffusion schedule |
Classifier-Guidance (Dhariwal and Nichol) | [✓] Training on CIFAR-10 [ㅤ] AdaGN [ㅤ] BiGGAN Upsample/Downsample [ㅤ] Improved DDPM sampling [ㅤ] Conditional/Unconditional models [ㅤ] Super-resolution model [ㅤ] Interpolation |
|
ILVR (Choi et al.) | [✓] Sampling using single reference [✓] Sampling using various downsampling factors [✓] Sampling using various conditioning range |
|
SDEdit (Meng et al.) | [✓] User input stroke simulation [✓] Applying CelebA at 64 × 64 [ㅤ] Total repeats. [ㅤ] VE SDEdit. [ㅤ] Sampling from scribble. [ㅤ] Image editing only on masked regions. |
|
MAE (He et al.) | [✓] Model architecture for self-supervised pre-training [✓] Model architecture for classification [ㅤ] Self-supervised pre-training on ImageNet-1K [ㅤ] Fine-tuning on ImageNet-1K [ㅤ] Linear probing |
|
Copy-Paste (Ghiasi et al.) | [✓] COCO dataset processing [✓] Large scale jittering [✓] Copy-Paste (within mini-batch) [✓] Visualizing data [ㅤ] Gaussian filter |
|
ViViT (Arnab et al.) | [✓] 'Spatio-temporal attention' architecture [✓] 'Factorised encoder' architecture [✓] 'Factorised self-attention' architecture |
|
2022 | CFG (Ho et al.) | |
Language | ||
2017 | Transformer (Vaswani et al.) | [✓] Model architecture [✓] Visualizing position encoding |
2019 | BERT (Devlin et al.) | [✓] Model architecture [✓] Masked language modeling [✓] BookCorpus data processing [✓] SQuAD data processing [✓] SWAG data processing |
Sentence-BERT (Reimers et al.) | [✓] Classification loss [✓] Regression loss [✓] Constrastive loss [✓] STSb data processing [✓] WikiSection data processing [ㅤ] NLI data processing |
|
RoBERTa (Liu et al.) | [✓] BookCorpus data processing [✓] Masked language modeling [ㅤ] BookCorpus data processing ('SEGMENT-PAIR' + NSP) [ㅤ] BookCorpus data processing ('SENTENCE-PAIR' + NSP) [✓] BookCorpus data processing ('FULL-SENTENCES') [ㅤ] BookCorpus data processing ('DOC-SENTENCES') |
|
2021 | Swin Transformer (Liu et al.) | [✓] Patch partition [✓] Patch merging [✓] Relative position bias [✓] Feature map padding [✓] Self-attention in non-overlapped windows [ㅤ] Shifted Window based Self-Attention |
2024 | RoPE (Su et al.) | [✓] Rotary Positional Embedding |
Vision-Language | ||
2021 | CLIP (Radford et al.) | [✓] Training on Flickr8k + Flickr30k [✓] Zero-shot classification on ImageNet1k (mini) [✓] Linear classification on ImageNet1k (mini) |
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train_easyocr
train_easyocr PublicFine-tuning 'EasyOCR' on the '공공행정문서 OCR' dataset provided by 'AI-Hub'.
1,159 contributions in the last year
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KimRass/StyleGAN
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