Awesome-AI-ART-generation

This is a collection of resources on AI-AR-ART generation with slides!

We are AI300 lab in ECE of Shanghai Jiao Tong University, and this is the sharing papers of research meeting and group discussion, including slides maded by ourselves.

Contributing

If you think I have missed out on something (or) have any suggestions (papers, implementations and other resources), feel free to pull a request.

Feedback and contributions are welcome!

GAN models

Papers	Conference	Year	Code	Speaker	Slides
Alias-Free Generative Adversarial Networks (StyleGAN3)	ICCV	2021	here	Xiaohang Wang	here
Anycost GANs for Interactive Image Synthesis and Editing	CVPR	2021	here	Yutian Liu	x
CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation	CVPR	2021	here	Jiyao Mao	here
Projected GANs Converge Faster	NIPS	2021	here	Yuhan Li	here
GAN-Supervised Dense Visual Alignment	arXiv	2021	here	Yuhan Li	here
HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping	IJCAI	2021	here	Yutian Liu	here
Correction Filter for Single Image Super-Resolution: Robustifying Off-the-Shelf Deep Super-Resolvers	CVPR	2020	here	Xiaohang Wang	here

GAN Edit Method

Papers	Conference	Year	Code	Speaker	Slides
How to Edit on Latent Space of GAN	x	x	x	Yuhan Li	here

DDPM related models

Papers	Conference	Year	Code	Speaker	Slides
ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models	ICCV	2021	here	Jiyao Mao	here
Denoising Diffusion Probabilistic Models	NIPS	2020	here	Zhilin Zeng	here
Vector Quantized Diffusion Model for Text-to-Image Synthesis	arXiv	2021	here	Zhilin Zeng	here
Latent Diffusion Models	arXiv	2021	here	Yuhan Li	here
Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes	arXiv	2021	here	Yuhan Li	here
Score-Based Generative Modeling through Stochastic Differential Equations	ICLR	2021	here	Yuhan Li	here
An Introduction About Diffusion Models	x	x	x	Yuhan Li	here

Deep Compression

Papers	Conference	Year	Code	Speaker	Slides
A survey about Deep Compression	x	x	x	Yutian Liu	here

Loss Landscape

Papers	Conference	Year	Code	Speaker	Slides
Visualizing the Loss Landscape of Neural Nets	NIPS	2018	here	Yutian Liu	here
How Do Vision Transformers Work?	ICLR	2022	here	Yutian Liu	here
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations	ICLR	2022	here	Yutian Liu	here
An Empirical Analysis of Deep Network Loss Surfaces	Machine Learning	2017	x	Yutian Liu	here

Nerf Related

Papers	Conference	Year	Code	Speaker	Slides
Plenoxels: Radiance Fields without Neural Networks	CVPR	2022	here	Xiaohang Wang	here
Point-NeRF: Point-based Neural Radiance Fields	CVPR	2022	here	Xiaohang Wang	here

Implicit Representations

Papers	Conference	Year	Code	Speaker	Slides
(Implicit) ^2: Implicit Layers for Implicit Representations	ICLR	2021	here	Xiaohang Wang	here

Text to image and CLIP

Papers	Conference	Year	Code	Speaker	Slides
CLIP: Learning Transferable Visual Models From Natural Language Supervision	arXiv	2021	here	Zhilin Zeng	here
StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery	ICCV	2021	here	Zhilin Zeng	here
CLIPDraw: Exploring Text-to-Drawing Synthesis through Language-Image Encoders	arXiv	2021	here	Ye Chen	here
StyleCLIPDraw: Coupling Content and Style in Text-to-Drawing Translation	arXiv	2022	here	Ye Chen	here
A survey about VectorDrawing	x	x	x	Jiyao Mao	here