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1. Resume

RESUME

2. Github Stats

KimRass' GitHub stats

3. 'Baekjoon Online Judge' Solved Rank

hyp3rflow's solved.ac stats

4. PyTorch Implementations From Scratch

Vision
2014 VAE Kingma and Welling [✓] Training on MNIST
[✓] Encoder output visualization
[✓] Decoder output visualization
2015 CAM Zhou et al. [✓] Application to GoogleNet
2016 Gatys et al., 2016 Gatys et al. [✓] Application to VGGNet-19
YOLO Redmon et al. [✗] Training on VOC 2012
[✗] Class probability map
[✗] Ground truth vlisualization on grid
DCGAN Radford et al. [✓] Training on CelebA at 64 × 64
[✓] Sampling
[✓] Latent space interpolation
Noroozi et al., 2016 Noroozi et al. [✓] Architecture
[✓] Chromatic aberration
[✓] Permutation set
Zhang et al., 2016 Zhang et al. [✓] Empirical probability distribution
[✗] Color space
2014
2017
Conditional GAN
WGAN-GP
Mirza et al.
Gulrajani et al.
[✓] Training on MNIST
2016
2017
PixelCNN
VQ-VAE
Oord et al.
Oord et al.
[✓] Training on Fashion MNIST
[✓] Training on CIFAR-10
2017 Pix2Pix Isola et al. [✓] Training on Google Maps
[✓] Training on Facades
[✗] Inference on larger resolution
CycleGAN Zhu et al. [✓] Training on Monet to photo
[✓] Training on Vangogh to photo
[✓] Training on Cezanne to photo
[✓] Training on Ukiyo-e to photo
[✓] Training on Horse to zebra
[✓] Training on Summer to winter
Noroozi et al., 2017 Noroozi et al. [✓] Constrastive loss
2018 PGGAN Karras et al. [✓] Training on CelebA-HQ at 512 × 512
DeepLab v3 Chen et al. [✓] Training on VOC 2012
[✓] Prediction on VOC 2012 validation set
[✓] Average mIoU
PixelLink Deng et al. [✓] Architecture
[✓] Instance-balanced cross entropy loss
[✓] Post-processing
RotNet Gidaris et al [✓] Attention map visualization
2020 STEFANN Roy et al. [✓] FANnet architecture
[✓]Training FANnet on Google Fonts
[✓] Custom Google Fonts dataset
[✓] Average SSIM
DDPM Ho et al. [✓] Training on CelebA at 32 × 32
[✓] Training on CelebA at 64 × 64
[✓] Denoising process visualization
[✓] Linear interpolation sampling
[✓] Coarse-to-fine sampling
DDIM Song et al. [✓] Sampling
[✓] Spherical interpolation sampling
[✓] Interpolation on grid sampling
[✓] Truncated normal
ViT Dosovitskiy et al. [✓] Training on CIFAR-10
[✓] Training on CIFAR-100
[✓] Attention Roll-out
[✓] Position embedding similarity
[✓] Position embedding interpolation
Extra
[✓] CutOut
[✓] Hide-and-Seek
[✓] CutMix
SimCLR Chen et al. [✓] Normalized temperature-scaled cross entropy loss
[✓] Data augmentation
[✓] Pixel intensity histogram
2021 Improved DDPM Nichol and Dhariwal [✓] Cosine diffusion schedule
Classifier-Guidance Dhariwal and Nichol [✗] AdaGN
[✗] BiGGAN Upsample/Downsample
[✗] Improved DDPM sampling
[✗] Conditional/Unconditional models
[✗] Super-resolution model
[✗] Interpolation
ILVR Choi et al. [✓] Sampling from single reference
[✓] Sampling from various scale factors
[✓] Sampling from various conditioning range
SDEdit Meng et al. [✓] User input stroke simulation
MAE He et al. [✓] MAE architecture for pre-training
[✗] MAE architecture for self-supervised learning
[✗] Training on ImageNet-1K
[✗] Fine-tuning
[✗] Linear probing
Copy-Paste Ghiasi et al. [✓] Large scale jittering
[✓] Copy-Paste (within mini-batch)
[✗] Gaussian filter
2022 CFG Ho et al.
Language
2017 Transformer Vaswani et al. [✓] Architecture
[✓] Position encoding visualization
2019 BERT Devlin et al. [✓] BookCorpus data pre-processing
[✓] Architecture
[✓] Masked language modeling
[✓] SQuAD data pre-processing
[✓]SWAG data pre-processing
Sentence-BERT Reimers et al. [✓] Classification loss
[✓] Regression loss
[✓] Constrastive loss
[✓] STSb data pre-processing
[✓] WikiSection data pre-processing
[✗] NLI data pre-processing
RoBERTa Liu et al. [✓] BookCorpus data pre-processing
[✓] Masked language modeling
[✗] BookCorpus data pre-processing
(SEGMENT-PAIR + NSP)
[✗] BookCorpus data pre-processing
(SENTENCE-PAIR + NSP)
[✓] BookCorpus data pre-processing
(FULL-SENTENCES)
[✗] BookCorpus data pre-processing
(DOC-SENTENCES)
Vision-Language
2021 CLIP Radford et al. [✓] Training on Flickr8k + Flickr30k
[✓] Zero-shot classification on ImageNet1k (mini)
[✓] Linear classification on ImageNet1k (mini)
Vision
2014 GAN Goodfellow et al.
2016 Context Encoder Pathak et al.
2022 BEiT Bao et al.
2022 Flamingo Alayrac et al.
2022 DiT Peebles et al.
2023 ContolNet Zhang et al.

Jongbeom Kim's Projects

algorithm-coding-test icon algorithm-coding-test

Algorithm practice problems from 'Baekjoon Online Judge' and 'Programmers' online judge and their solutions in Python

bert icon bert

'BERT' (Devlin et al., 2019) implementation from scratch in PyTorch

cam icon cam

PyTorch implementation of 'CAM' (Zhou et al., 2015) from scratch.

cfg icon cfg

PyTorch implementation of 'CFG' (Ho et al., 2022).

clip icon clip

PyTorch implementation of 'CLIP' (Radford et al., 2021) from scratch and training it on Flickr8k + Flickr30k

conditional-wgan-gp icon conditional-wgan-gp

PyTorch implementation of 'Conditional GAN' (Mirza et al., 2014) & 'WGAN-GP' (Gulrajani et. al., 2017) and training it on MNIST

copy-paste icon copy-paste

From-scratch PyTorch implementation of 'Copy-Paste' (Ghiasi et al., 2021) on COCO 2014.

cyclegan icon cyclegan

PyTorch implementation of 'CycleGAN' (Zhu et al., 2017) and training it on 6 datasets

dcgan icon dcgan

PyTorch implementation of 'DCGAN' (Radford et al., 2016) and training it on CelebA

ddim icon ddim

PyTorch implementation of 'DDIM' (Jiaming Song et al., 2020).

ddpm icon ddpm

PyTorch implementation of 'DDPM' (Ho et al., 2020) and training it on CelebA 64×64

deeplabv3 icon deeplabv3

PyTorch implementation of 'DeepLabv3' (Chen et al., 2018) and training it on VOC 2012

detr icon detr

'DETR' (Carion et al., 2020) implementation from scratch in PyTorch

dl_based_image_recognition_model icon dl_based_image_recognition_model

This repository is based on the lecture '딥러닝 기반의 영상 인식 모델 구현'

ilvr icon ilvr

PyTorch implementation of 'ILVR' (Choi et al., 2021) from scratch and applying it to 'DDPM' on CelebA at 64 × 64

improved-ddpm icon improved-ddpm

PyTorch implementation of 'Improved DDPM' (Nichol and Dhariwal, 2021).

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