Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+---
+# Learnable SMPLify: A Neural Solution for Optimization-Free Human Pose Inverse Kinematics
+
+#### <p align="center">[arXiv Paper](https://arxiv.org/abs/2508.13562)</p>
+
+``TL;DR`` Given X_{t-s} and X_{t} 3D keypoints, 
+calculate residual SMPL parameters from t-s to t.
+
+## Preparation
+Refer to [PREPARATION.md](doc/PREPARATION.md) for installation and data preparation details.
+
+## Checkpoints
+The pretrained model checkpoint is available at [Google Drive](https://drive.google.com/drive/folders/1oyG2gbB3EMcc6NgTIT1p1uJ_Em0dJwXz?usp=sharing).
+
+## Usage
+### Training
+cd to `src` folder and run the following command.
+
+```
+torchrun --nproc-per-node <NUM_GPUS> main.py --config configs/net.yaml (--extra_tag <EXTRA_TAG> --batch_size <BATCH_SIZE> --epochs <EPOCHS>)
+```
+
+You can get logs, tensorboard and checkpoints in the corresponding `logs/<MODEL_NAME>_net_<EXTRA_TAG>` folder.
+
+### Evaluation
+To evaluate the model, run the following command:
+
+```
+torchrun --nproc-per-node <NUM_GPUS> main.py --config configs/net.yaml --eval --checkpoint <PATH_TO_CHECKPOINT>
+```
+
+### Sequential Inference
+To run sequential inference, you can use the following command:
+
+```
+python inference.py <PATH_TO_CHECKPOINT> (<DATASET_NAME> <SAMPLE_RATIO>)
+```
+
+## Citation
+If you find this work useful in your research, please consider citing:
+
+```
+@misc{LearnableSMPLify,
+      title={Learnable SMPLify: A Neural Solution for Optimization-Free Human Pose Inverse Kinematics},
+      author={Yuchen, Yang and Linfeng, Dong and Wei, Wang and Zhihang, Zhong and Xiao, Sun},
+      year={2025},
+      eprint={2508.13562},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```
+
+## Acknowledgement
+We thank the authors of [ST-GCN](https://github.com/open-mmlab/mmskeleton), [ReFit](https://github.com/yufu-wang/ReFit), [OSX](https://github.com/IDEA-Research/OSX/tree/main) for their great works. We partially refer to their codebases for this project.