From f9b29c54b334e2d8404ede6a5badab6bc747dd22 Mon Sep 17 00:00:00 2001 From: xuzhen Date: Sun, 21 Jan 2024 16:23:34 +0800 Subject: [PATCH] update tpami links & citation --- README.md | 16 ++++++++++++++-- 1 file changed, 14 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index e10804f..2578adc 100644 --- a/README.md +++ b/README.md @@ -6,12 +6,16 @@ * `07/09/2022` We release the [extended version](https://arxiv.org/abs/2203.08133) of Animatable NeRF. We evaluated three different versions of Animatable Neural Fields, including vanilla Animatable NeRF, a version where the neural blend weight field is replaced with displacement field and a version where the canonical NeRF model is replaced with a neural surface field (output is SDF instead of volume density, also using displacement field). We also provide evaluation framework for reconstruction quality comparison. * `10/28/2021` To make the comparison with Animatable NeRF easier on the Human3.6M dataset, we save the quantitative results at [here](https://zjueducn-my.sharepoint.com/:f:/g/personal/pengsida_zju_edu_cn/EpW0AHZh1OtDoa-vTaaCAYgBddyACEICg-941VYgyASk7g?e=W4KvSK), which also contains the results of other methods, including Neural Body, D-NeRF, Multi-view Neural Human Rendering, and Deferred Neural Human Rendering. -# Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies +# Animatable Implicit Neural Representations for Creating Realistic Avatars from Videos -### [Project Page](https://zju3dv.github.io/animatable_nerf) | [Video](https://www.youtube.com/watch?v=eWOSWbmfJo4) | [Paper](https://arxiv.org/abs/2105.02872) | [Data](https://github.com/zju3dv/animatable_nerf/blob/master/INSTALL.md#zju-mocap-dataset) | [Extension](https://arxiv.org/abs/2203.08133) +### [Project Page](https://zju3dv.github.io/animatable_sdf) | [Video](https://www.youtube.com/watch?v=eWOSWbmfJo4) | [Paper](https://arxiv.org/abs/2203.08133) | [Data](https://github.com/zju3dv/animatable_nerf/blob/master/INSTALL.md#zju-mocap-dataset) | [ICCV21](https://zju3dv.github.io/animatable_nerf) ![teaser](https://zju3dv.github.io/animatable_nerf/images/github_teaser.gif) +> [Animatable Implicit Neural Representations for Creating Realistic Avatars from Videos](https://arxiv.org/abs/2203.081332) +> Sida Peng, Zhen Xu, Junting Dong, Qianqian Wang, Shangzhan Zhang, Qing Shuai, Hujun Bao, Xiaowei Zhou +> TPAMI 2024 + > [Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies](https://arxiv.org/abs/2105.02872) > Sida Peng, Junting Dong, Qianqian Wang, Shangzhan Zhang, Qing Shuai, Xiaowei Zhou, Hujun Bao > ICCV 2021 @@ -219,6 +223,14 @@ Since the license of the [RenderPeople](https://renderpeople.com/) dataset does If you find this code useful for your research, please use the following BibTeX entry. ```bibtex +@article{peng2024animatable, + title={Animatable Implicit Neural Representations for Creating Realistic Avatars from Videos}, + author={Peng, Sida and Xu, Zhen and Dong, Junting and Wang, Qianqian and Zhang, Shangzhan and Shuai, Qing and Bao, Hujun and Zhou, Xiaowei}, + journal={TPAMI}, + year={2024}, + publisher={IEEE} +} + @inproceedings{peng2021animatable, title={Animatable Neural Radiance Fields for Modeling Dynamic Human Bodies}, author={Peng, Sida and Dong, Junting and Wang, Qianqian and Zhang, Shangzhan and Shuai, Qing and Zhou, Xiaowei and Bao, Hujun},