'23 Individual Research
1.Stable Diffusion(1) - Generative Model Basics
Basic Generative Models : PixelRNN, PixelCNN, Autoencoder, VAE, GAN
2.Stable Diffusion(2) - Diffusion Models
Diffusion Models : Diffusion Process, DDPM, DDIM, Score-Based Model
3.Stable Diffusion(3) - Conditioning Algorithms
Conditioning Algorithm : Attention, Classifier-Free Algorithm
4.Stable Diffusion(4) - Stable Diffusion
Stable Diffusion paper review
5.Stable Diffusion(5) - Seminar
Slides about Stable Diffusion
6.NVP(1) - Paper Review
Scalable Neural Video Representations with Learnable Positional Features paper review
7.NVP(2) - Code Execution
Running the NVP code included in the paper
8.NVP(3) - Ideas Proposal
Ideas for applying the NVP model worth trying out
9.NVP(4) - Experiments
Implementation and experimentation of the devised ideas
10.NVP(5) - Seminar
Slides about idea proposal for NVP model
11.NVP2(1) - Ideas Proposal on Sparse Positional Features
Ideas proposal on sparse positional feature of the NVP model
12.NVP2(2) - Remote Server Connection
Connecting to the research server to run the NVP code
13.NVP2(3) - Codec Basics
Basic knowledge about video codecs
14.NVP2(4) - Tucker Decomposition
Basic concept of Tucker decomposition
15.NVP2(5) - Experiments
Implementation and experimentation of the devised ideas
16.NVP2(6) - Seminar
Slides about experiment results of size reduction of sparse grid
17.NVP3(1) - Additional Ideas Proposal on Sparse Positional Features
Additional ideas proposal on sparse positional feature of the NVP model
18.NVP3(2) - Experiments
Implementation and experimentation of the ideas
19.NVP3(3) - Seminar
Slides about experiment results of compression guidance