https://github.com/choidae1/paper-review

Repo for Computer Vision Paper review
https://github.com/choidae1/paper-review

computer-vision paper paper-review

Last synced: about 1 month ago
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Repo for Computer Vision Paper review

• Host: GitHub
• URL: https://github.com/choidae1/paper-review
• Owner: ChoiDae1
• Created: 2021-11-30T00:23:18.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2023-01-05T13:08:51.000Z (almost 2 years ago)
• Last Synced: 2023-03-08T15:13:05.028Z (almost 2 years ago)
• Topics: computer-vision, paper, paper-review
• Homepage:
• Size: 50.8 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# paper-review

This repository is a space for **reviewing various papers.** (e.g CV, Deeplearning, XAI etc)

 All contents of the paper review will uploaded at my blog. -> [link](https://science886.tistory.com/category/Paper%20review)

 In this README.md file, the address of the review of the each paper will be attached. 

|Date|Paper Title|Review Link|

|------|---|---|

|2021.12.27|[Image Style Transfer Using Convolutional Neural Networks](https://openaccess.thecvf.com/content_cvpr_2016/html/Gatys_Image_Style_Transfer_CVPR_2016_paper.html)| https://science886.tistory.com/2 |

|2022.01.06|[An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://arxiv.org/abs/2010.11929)| https://science886.tistory.com/7 |

|2022.01.08|[MLP-Mixer An all-MLP Architecture for Vision](https://arxiv.org/abs/2105.01601)| https://science886.tistory.com/9 |

|2022.01.12|[Mask R-CNN](https://arxiv.org/abs/1703.06870)| https://science886.tistory.com/10|

|2022.01.18|[End-to-End Object Detection with Transformers](https://arxiv.org/abs/2005.12872)| https://science886.tistory.com/11|

|2022.01.19|[Vision Transfomers for Dense Prediction](https://arxiv.org/abs/2103.13413)| https://science886.tistory.com/12|

|2022.01.21|[NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis](https://arxiv.org/abs/2003.08934)| https://science886.tistory.com/13|

|2022.01.26|[A Style-Based Generator Architecture for Generative Adversarial Networks](https://arxiv.org/abs/1812.04948)| https://science886.tistory.com/14|

|2022.02.08|[GLIDE: Toward Photorealistic Image Generation and Editing with Text-Guided Diffusion Models](https://arxiv.org/abs/2112.10741)| https://science886.tistory.com/17|

|2022.02.15|[CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fields](https://arxiv.org/abs/2112.05139)| https://science886.tistory.com/19|

|2022.02.16|[Digging Into Self-Supervised Monocular Depth Estimation](https://arxiv.org/abs/1806.01260)| https://science886.tistory.com/20|

|2022.02.22|[Attention Is All You Need](https://arxiv.org/abs/1706.03762)| https://science886.tistory.com/21|

|2022.03.13|[Point-NeRF: Point-based Neural Radiance Fields](https://arxiv.org/abs/2201.08845)| https://science886.tistory.com/23|

|2022.03.18|[Improving neural implicit surfaces geometry with patch warping](https://arxiv.org/abs/2112.09648)| https://science886.tistory.com/26|

|2022.05.03|[Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation](https://arxiv.org/abs/2008.00951)| https://science886.tistory.com/30|

|2022.05.04|[Designing an Encoder for StyleGAN Image Manipulation](https://arxiv.org/abs/2102.02766)| https://science886.tistory.com/31|

|2022.06.24|[Pivotal Tuning for Latent-based Editing of Real Images](https://arxiv.org/abs/2106.05744)| https://science886.tistory.com/34|

|2022.07.11|[High-Fidelity GAN Inversion for Image Attribute Editing](https://arxiv.org/abs/2109.06590)| https://science886.tistory.com/35|

|2022.07.14|[Spatially-Adaptive Multilayer Selection for GAN Inversion and Editing](https://arxiv.org/abs/2206.08357)| https://science886.tistory.com/36|

|2022.07.21|[LARGE: Latent-Based Regression through GAN Semantics](https://arxiv.org/abs/2107.11186)| https://science886.tistory.com/38|

|2022.07.22|[Efficient Geometry-aware 3D Generative Adversarial Networks](https://arxiv.org/abs/2112.07945)| https://science886.tistory.com/39|

|2022.01.03|[Model-Agnostic Meta-learning for Fast Adaptation of Deep Networks](https://arxiv.org/abs/1703.03400)| https://science886.tistory.com/42|

|2022.01.05|[FEW-SHOT ACOUSTIC EVENT DETECTION VIA META LEARNING](https://arxiv.org/abs/1703.03400)| https://science886.tistory.com/44|