update tpami links & citation

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},