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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This repository is a curated collection of the most exciting and influential CVPR 2023 papers. 🔥 [Paper + Code]
| Date | Stars |
|---|---|
| 2026-07-24 | 648 |
| 2026-07-25 | 648 |
| 2026-07-28 | 648 |
| 2026-07-30 | 648 |
| 2026-08-06 | 648 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
<div align="center">
<h1 align="center">top CVPR 2023 papers</h1>
<a href="https://github.com/SkalskiP/top-cvpr-2023-papers">2023</a> | <a href="https://github.com/SkalskiP/top-cvpr-2024-papers">2024</a> | <a href="https://github.com/SkalskiP/top-cvpr-2025-papers">2025</a> | <a href="https://github.com/SkalskiP/top-cvpr-2026-papers">2026</a>
</div>
<p align="center">
</br>
<img width="600" src="https://github.com/SkalskiP/top-cvpr-2023-papers/assets/26109316/2d7be39e-11a0-4298-ad90-c0645af0c5ac" alt="vancouver">
</br>
</p>
## 👋 hello
Computer Vision and Pattern Recognition is a massive conference. In **2023** alone, **9,155** papers were submitted, and **2,359** were accepted. I created this repository to help you search for crème de la crème of CVPR publications. If the paper you are looking for is not on my short list, take a peek at the full [list](https://cvpr.thecvf.com/Conferences/2023/AcceptedPapers) of accepted papers.
## 🗞️ papers
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| **topic** | **title** | **repository / paper** |
|:---------:|:---------:|:----------------------:|
| Segmentation | OneFormer: One Transformer To Rule Universal Image Segmentation | [](https://github.com/SHI-Labs/OneFormer) [](https://arxiv.org/abs/2211.06220)|
| Segmentation | X-Decoder: Generalized Decoding for Pixel, Image and Language | [](https://github.com/microsoft/X-Decoder) [](https://arxiv.org/abs/2212.11270)|
| Segmentation and Generative AI | Images Speak in Images: A Generalist Painter for In-Context Visual Learning | [](https://github.com/baaivision/Painter) [](https://arxiv.org/abs/2212.02499)|
| Segmentation | PACO: Parts and Attributes of Common Objects | [](https://github.com/facebookresearch/paco) [](https://arxiv.org/abs/2301.01795)|
| Segmentation | Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP | [](https://github.com/facebookresearch/ov-seg) [](https://arxiv.org/abs/2210.04150)|
| NeRF | DynIBaR: Neural Dynamic Image-Based Rendering | [](https://github.com/google/dynibar) [](https://arxiv.org/abs/2211.11082)|
| 3D | Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition | [](https://github.com/MoyGcc/vid2avatar) [](https://arxiv.org/abs/2302.11566)|
| Generative AI | 3D-aware Conditional Image Synthesis | [](https://github.com/dunbar12138/pix2pix3d) [](https://arxiv.org/abs/2302.08509)|
| 3D | 3D Human Mesh Estimation from Virtual Markers | [](https://github.com/Excerpt of 7,754 characters
Read on GitHub
Piotr Skalski · @roboflow
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2bbebdd67d6f2f01, topic:computer-vision, topic:object-detection, topic:image-segmentation