Update README.md

README.md

@@ -8,6 +8,7 @@ tags:
   - RGBD
   - SMPL
   - motion-capture
+  - VR
 size_categories:
   - 10K<n<100K
 ---
@@ -16,53 +17,56 @@ size_categories:
 
 ## Overview
 
-This dataset contains egocentric RGBD sequences for 3D human pose estimation from a first-person VR perspective.
+The **EgoPoseVR Dataset** is a large-scale synthetic dataset for egocentric full-body pose estimation in virtual reality.  
+It contains paired RGB-D observations, pose annotations, HMD tracking signals, and SMPL body parameters for temporally aligned motion clips.
+
+![Pipeline](assets/images/EgoPoseVR.jpg)
 
 - **Total samples**: 18,235 motion clips
-- **Scenes**: 7 virtual scenes (Scene0 - Scene6)
+- **Scenes**: 7 virtual scenes (`Scene0` - `Scene6`)
 - **Train / Val / Test**: 14,702 / 1,827 / 1,706
 - **Total size**: ~362 GB
 - **Data format**: `.npz` (NumPy compressed archives)
 
+For more details, please visit the [Project Page](https://aplusx.github.io/EgoPoseVRWeb/) or check the [official repository](https://aplusx.github.io/EgoPoseVRWeb/).
+
+---
+
 ## Data Sources
-- CMU Graphics Lab Motion Capture Database
-- BioMotionLab (NTroje) Dataset
+
+The motion data is derived from the [AMASS](https://amass.is.tue.mpg.de/) dataset.  
+In total, **2,344 motion sequences** are extracted. Each sequence folder corresponds to one continuous motion sequence, and each `.npz` file contains a 100-frame clip sampled from that sequence.
+
+---
 
 ## Directory Structure
 
-```
+```text
 EgoPoseVR_Dataset/
-├── Scene{0-6}/                             # 7 virtual scenes
-│   └── AllDataPath_{Source}_{split}_{id}/  # motion sequence directory
-│       └── {clip_id}.npz                    # motion clip file
+├── Scene0/
+├── Scene1/
+├── Scene2/
+├── Scene3/
+├── Scene4/
+├── Scene5/
+├── Scene6/
+│   └── AllDataPath_{Source}_{split}_{id}/
+│       └── {clip_id}.npz
 ├── train_npz_paths.txt
 ├── val_npz_paths.txt
 ├── test_npz_paths.txt
 └── all_npz_paths.txt
 ```
 
-## NPZ Fields
-
-Each `.npz` file represents a motion clip with T consecutive frames (typically T=100).
+## Citation
 
-| Field | Shape | Description |
-|---|---|---|
-| `input_rgbd` | (T, 4, H, W) | Input RGBD image sequence (channels 0-2: RGB normalized to [0,1]; channel 3: depth) |
-| `gt_joints_relativeCam_2Dpos` | (T, 22, 2) | GT joint 2D positions projected to camera image plane |
-| `gt_joints_relativePelvis_3Dpos` | (T, 22, 3) | GT joint 3D positions relative to pelvis (pelvis at origin) |
-| `gt_pelvis_camera_3Dpos` | (T, 3) | GT pelvis 3D position in camera coordinate system |
-| `gt_pelvis_camera_4Drot` | (T, 4) | GT pelvis rotation in camera space (quaternion) |
-| `hmd_position_global_full_gt_list` | (T, 54) | HMD global position/orientation data (head + hands) |
-| `head_global_trans_list` | (T, 4, 4) | Head global 4x4 transformation matrices per frame |
-| `body_parms_list` | dict | SMPL body parameters (root_orient, pose_body, trans) |
-| `pred_2d` | (T, 22, 2) | Predicted 2D joint positions from pretrained estimator |
-| `pred_3d` | (T, 22, 3) | Predicted 3D joint positions from pretrained estimator |
+If you find our code or paper helps, please consider citing:
 
-## Joint Definition (22 SMPL joints)
-
-```
-0:Pelvis  1:L_Hip  2:R_Hip  3:Spine1  4:L_Knee  5:R_Knee
-6:Spine2  7:L_Ankle  8:R_Ankle  9:Spine3  10:L_Foot  11:R_Foot
-12:Neck  13:L_Collar  14:R_Collar  15:Head  16:L_Shoulder  17:R_Shoulder
-18:L_Elbow  19:R_Elbow  20:L_Wrist  21:R_Wrist
+```bibtex
+@article{cheng2026egoposevr,
+  title={EgoPoseVR: Spatiotemporal Multi-Modal Reasoning for Egocentric Full-Body Pose in Virtual Reality},
+  author={Cheng, Haojie and Ong, Shaun Jing Heng and Cai, Shaoyu and Koh, Aiden Tat Yang and Ouyang, Fuxi and Khoo, Eng Tat},
+  journal={arXiv preprint arXiv:2602.05590},
+  year={2026}
+}
 ```