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Awesome Machine Learning Papers
https://github.com/shovelingpig/awesome-ml-papers
List: awesome-ml-papers
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Awesome Machine Learning Papers
- Host: GitHub
- URL: https://github.com/shovelingpig/awesome-ml-papers
- Owner: shovelingpig
- Created: 2022-04-04T00:34:48.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2022-04-06T22:39:16.000Z (over 2 years ago)
- Last Synced: 2024-04-09T20:53:39.157Z (5 months ago)
- Size: 63.5 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- ultimate-awesome - awesome-ml-papers - Awesome Machine Learning Papers. (Other Lists / PowerShell Lists)
README
# Awesome Machine Learning Papers
## Contributing
markdown format:
``` markdown
**Here is the Paper Name.**
*[Author 1](homepage), Author 2, and Author 3.*
Conference or Journal Year. [[PDF](link)] [[Project](link)] [[Github](link)] [[Video](link)] [[Data](link)]
```
## CNN
- (ResNet) [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385)
## RNN
- (GRU) [Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling](https://arxiv.org/abs/1412.3555)
## Transformer
- (Transformer) [Attention Is All You Need](https://arxiv.org/abs/1706.03762)
- (ViT) [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030)
## AE
- (VAE) [Auto-Encoding Variational Bayes](https://arxiv.org/abs/1312.6114)
## GAN
- (GAN) [Generative Adversarial Networks](https://arxiv.org/abs/1406.2661)
- (ProgressiveGAN) [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://arxiv.org/abs/1710.10196)
- (StyleGAN) [A Style-Based Generator Architecture for Generative Adversarial Networks](https://arxiv.org/abs/1812.04948)
- (StyleGAN2) [Analyzing and Improving the Image Quality of StyleGAN](https://arxiv.org/abs/1912.04958)
- (StyleGAN2-Ada) [Training Generative Adversarial Networks with Limited Data](https://arxiv.org/abs/2006.06676)
- (StyleGAN3) [Alias-Free Generative Adversarial Networks](https://nvlabs.github.io/stylegan3/)
- [StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2](https://arxiv.org/abs/2112.14683)
## Flow
- (Normalizing Flow) [Variational Inference with Normalizing Flows](https://ar5iv.labs.arxiv.org/html/1505.05770)
- [Glow: Generative Flow with Invertible 1x1 Convolutions](https://arxiv.org/abs/1807.03039)
## Diffusion
- (DDPM) [Diffusion Models Beat GANs on Image Synthesis](https://arxiv.org/pdf/2105.05233v4.pdf)
## 3DMM
> 3D Morphable Model
- (BFM) [Morphable Face Models - An Open Framework](https://arxiv.org/abs/1709.08398)
- (FLAME) [Learning a model of facial shape and expression from 4D scans](https://ps.is.mpg.de/uploads_file/attachment/attachment/400/paper.pdf)
- [SMPL: A Skinned Multi-Person Linear Model](https://files.is.tue.mpg.de/black/papers/SMPL2015.pdf)
## NeRF
> Neural Radiance Field
- [NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](https://arxiv.org/abs/2003.08934)
- (Instant-NDP) [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.pdf)
- (DietNeRF) [Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis](https://ajayj.com/dietnerf)
- [Point-NeRF: Point-based Neural Radiance Fields](https://xharlie.github.io/projects/project_sites/pointnerf/index.html)
- [StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generation](https://arxiv.org/abs/2112.11427)
- [A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose](https://openreview.net/pdf?id=lwwEh0OM61b)
## Normalization
- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://arxiv.org/abs/1502.03167)
- [Layer Normalization](https://arxiv.org/abs/1607.06450)
## Representation Learning
- [Retriever: Learning Content-Style Representation as a Token-Level Bipartite Graph](https://arxiv.org/abs/2202.12307)
## Contrastive Learning
- (SimCLR) [A Simple Framework for Contrastive Learning of Visual Representations](https://arxiv.org/abs/2002.05709)
- (SimCLR2) [Big Self-Supervised Models are Strong Semi-Supervised Learners](https://arxiv.org/abs/2006.10029)
## INR
> Implicit Neural Representation
- (Functa) [From data to functa: Your data point is a function and you should treat it like one](https://arxiv.org/abs/2201.12204)
## SR
> Super Resolution
- (GPEN) [GAN Prior Embedded Network for Blind Face Restoration in the Wild](https://arxiv.org/abs/2105.06070)
## Face Recognition
- [ArcFace: Additive Angular Margin Loss for Deep Face Recognition](https://arxiv.org/abs/1801.07698)
- [CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition](https://arxiv.org/abs/2004.00288)
- [GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition](https://arxiv.org/abs/2005.10497)
## Facial Editting
- (STIT) [Stitch it in Time: GAN-Based Facial Editing of Real Videos](https://stitch-time.github.io/)
## Talking Head
- (SAFA) [SAFA: Structure Aware Face Animation](https://arxiv.org/abs/2111.04928)
## Face Swapping
- [SimSwap: An Efficient Framework For High Fidelity Face Swapping](https://arxiv.org/abs/2106.06340)
- [HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping](https://arxiv.org/abs/2106.09965)
- [FaceInpainter: High Fidelity Face Adaptation to Heterogeneous Domains](https://openaccess.thecvf.com/content/CVPR2021/papers/Li_FaceInpainter_High_Fidelity_Face_Adaptation_to_Heterogeneous_Domains_CVPR_2021_paper.pdf)
- [One Shot Face Swapping on Megapixels](https://arxiv.org/abs/2105.04932)
- [ShapeEditer: a StyleGAN Encoder for Face Swapping](https://arxiv.org/abs/2106.13984)
- [FaceController: Controllable Attribute Editing for Face in the Wild](https://arxiv.org/abs/2102.11464)
- [High-Resolution Neural Face Swapping for Visual Effects](https://studios.disneyresearch.com/wp-content/uploads/2020/06/High-Resolution-Neural-Face-Swapping-for-Visual-Effects.pdf)
- [FSGAN: Subject Agnostic Face Swapping and Reenactment](https://arxiv.org/abs/1908.05932)
- [FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping](https://arxiv.org/abs/1912.13457)
- [Towards Open-Set Identity Preserving Face Synthesis](https://arxiv.org/abs/1803.11182)
- [RSGAN: Face Swapping and Editing using Face and Hair Representation in Latent Spaces](https://arxiv.org/abs/1804.03447)
- [FSNet: An Identity-Aware Generative Model for Image-based Face Swapping](https://arxiv.org/abs/1811.12666)
- [DeepFaceLab: Integrated, flexible and extensible face-swapping framework](https://arxiv.org/abs/2005.05535)
- [Deepfakes for Medical Video De-Identification: Privacy Protection and Diagnostic Information Preservation](https://arxiv.org/abs/2003.00813)
- [On Face Segmentation, Face Swapping, and Face Perception](https://arxiv.org/abs/1704.06729)
- SMILE
- Smooth-Swap
- FaceSwappingGAN
- SberSwap
## Background Editting
- [Omnimatte: Associating Objects and Their Effects in Video](https://omnimatte.github.io/)