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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.
IJCAI2023 - Collaborative Neural Rendering using Anime Character Sheets
| Date | Stars |
|---|---|
| 2026-07-24 | 805 |
| 2026-07-25 | 805 |
| 2026-07-28 | 805 |
| 2026-07-30 | 805 |
| 2026-08-06 | 805 |
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[English](https://github.com/megvii-research/CoNR/blob/main/README.md) | [中文](https://github.com/megvii-research/CoNR/blob/main/README_chinese.md) # Collaborative Neural Rendering using Anime Character Sheets Our paper is accepted by [Special Track of IJCAI2023](https://ijcai-23.org/special-track-on-ai-the-arts-and-creativity/) (three reviews with "accept" ratings), the revision of the paper is [available](https://arxiv.org/abs/2207.05378). -> [poster](https://drive.google.com/file/d/140eVtOPv0tl7l1ptmExEfuNAEu2JN_Wd/view?usp=sharing) 2023/4/18: The dataset is now avaliable in [CoNR_Dataset](https://github.com/P2Oileen/CoNR_Dataset)! 🎉 ## [Demo Page](https://transpchan.github.io/live3d/) | Colab [English](https://colab.research.google.com/github/megvii-research/CoNR/blob/main/notebooks/conr.ipynb)/[中文](https://colab.research.google.com/github/megvii-research/CoNR/blob/main/notebooks/conr_chinese.ipynb) | [arXiv](https://arxiv.org/abs/2207.05378) | [BiliBili](https://www.bilibili.com/video/BV19V4y1x7bJ/) | [YouTube](https://youtu.be/Z4HXWBF7mLI) | [CoNR_Dataset](https://github.com/P2Oileen/CoNR_Dataset)    ## Introduction This project is the official implement of [Collaborative Neural Rendering using Anime Character Sheets](https://arxiv.org/abs/2207.05378), which aims to genarate vivid dancing videos from hand-drawn anime character sheets (ACS).[^1] Watch more demos and details in our firmly recommended video in [BiliBili](https://www.bilibili.com/video/BV19V4y1x7bJ/) or [YouTube](https://youtu.be/Z4HXWBF7mLI). Our [FAQ on Zhihu (in Chinese)](https://zhuanlan.zhihu.com/p/565391665) explains the ideas underpinning CoNR. ## Usage #### Prerequisites * NVIDIA GPU + CUDA + CUDNN * Python 3.6 #### Installation * Clone this repository ```bash git clone https://github.com/megvii-research/CoNR ``` * Dependencies To install all the dependencies, please run the following commands. ```bash cd CoNR pip install -r requirements.txt ``` * Download Weights Download weights from Google Drive. Alternatively, you can download from [Baidu Netdisk](https://pan.baidu.com/s/1U11iIk-DiJodgCveSzB6ig?pwd=RDxc) (password:RDxc). ``` mkdir weights && cd weights gdown https://drive.google.com/uc?id=1M1LEpx70tJ72AIV2TQKr6NE_7mJ7tLYx gdown https://drive.google.com/uc?id=1YvZy3NHkJ6gC3pq_j8agcbEJymHCwJy0 gdown https://drive.google.com/uc?id=1AOWZxBvTo9nUf2_9Y7Xe27ZFQuPrnx9i gdown https://drive.google.com/uc?id=19jM1-GcqgGoE1bjmQycQw_vqD9C5e-Jm ``` #### Prepare Inputs We provide two Ultra-Dense Pose sequences for two characters. You can generate more UDPs via 3D models and motions refers to [our paper](https://arxiv.org/abs/2207.05378), or use [MMD2UDP](https://github.com/KurisuMakise004/MMD2UDP)(Thanks to @KurisuMakise004 ). [Baidu Netdisk](https://pan.baidu.com/s/1hWvz4iQXnVTaTSb6vu1NBg?pwd=RDxc) (password:RDxc) ``` # for short hair girl gdown https://drive.google.com/uc?id=11HMSaEkN__QiAZSnCuaM6GI143xo62KO unzip short_hair.zip mv short_hair/ poses/ # for double ponytail girl gdown https://drive.google.com/uc?id=1WNnGVuU0ZLyEn04HzRKzITXqib1wwM4Q unzip double_ponytail.zip mv double_ponytail/ poses/ ``` We provide sample inputs of anime character sheets. You can also draw more by yourself. Character sheets need to be cut out from the background and in png format. [Baidu Netdisk](https://pan.baidu.com/s/1shpP90GOMeHke7MuT0-Txw?pwd=RDxc) (password:RDxc) ``` # for short hair girl gdown https://drive.google.com/uc?id=1r-3hUlENSWj81ve2IUPkRKNB81o9WrwT unzip short_hair_images.zip mv short_hair_images/ character_sheet/ # for double ponytail girl gdown https://drive.google.com/uc?id=1XMrJf9Lk_dWgXyTJhbEK2LZIXL9G3MWc unzip double_ponytail_images.zip mv double_ponytail_images/ character_sheet/ ``` #### RUN! * with web UI (powered by [Streamlit](https://streamlit.io/)) ``` streamlit run streamlit.py --server.port=8501 ``` then open your browser and visit `localhost:8501`, follo
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hzwer · @stepfun-ai
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Shuchang Zhou · China
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:80087857eecdbdf8, topic:deep-learning, topic:pytorch
matched fp:80087857eecdbdf8, topic:computer-vision