Add dataset card

README.md

@@ -19,9 +19,26 @@ library_name: GRAIL
 
 # Dataset Overview
 
+| Tabletop Pickup | Ground Pickup |
+|:---:|:---:|
+| <img src="assets/videos/pickup_table.gif" width="420"/> | <img src="assets/videos/pickup_ground.gif" width="420"/> |
+
+| Tabletop Manipulation | Ground Manipulation |
+|:---:|:---:|
+| <img src="assets/videos/manip_tabletop.gif" width="420"/> | <img src="assets/videos/manip_large.gif" width="420"/> |
+
+| Sitting | Curb |
+|:---:|:---:|
+| <img src="assets/videos/sitting.gif" width="420"/> | <img src="assets/videos/terrain_curbs.gif" width="420"/> |
+
+| Slope | Stairs |
+|:---:|:---:|
+| <img src="assets/videos/terrain_slopes.gif" width="420"/> | <img src="assets/videos/terrain_stairs.gif" width="420"/> |
+
 ###  Description:
 
-**GRAIL** (**G**enerating Humanoid Loco-Manipulation from Video **F**oundation Models) is a dataset of physics-validated 4D human-object interaction (HOI) trajectories retargeted to the **Unitree G1** humanoid robot. Each motion is the output of an end-to-end pipeline that (1) generates a synthetic interaction video from a 3D asset, (2) reconstructs the underlying 4D HOI (SMPL-X human pose + object 6-DoF) from that video, (3) retargets the human motion to the G1 skeleton, and (4) validates the trajectory in physics simulation by training a reinforcement-learning (RL) tracker against it — the released motion data is the output of the RL tracking policy.
+**GRAIL** (Generating Humanoid Loco-Manipulation from 3D
+Assets and Video Priors) is a dataset of physics-validated 4D human-object interaction (HOI) trajectories for **Unitree G1** humanoid robot. Each motion is the output of an end-to-end pipeline that (1) generates a synthetic interaction video from a 3D asset, (2) reconstructs the underlying 4D HOI (SMPL-X human pose + object 6-DoF) from that video, (3) retargets the human motion to the G1 skeleton, and (4) validates the trajectory in physics simulation by training a reinforcement-learning (RL) tracker against it — the released motion data is the output of the RL tracking policy.
 
 The release is partitioned by HOI category. Each motion ships with: the source synthetic video, the 4D HOI reconstruction (SMPL-X + object pose), the retargeted G1 robot trajectory, the post-RL object trajectory, and the object's USD asset (textures preserved). This layout is byte-compatible with the GRAIL training stack, so the release can be dropped into a `motion_lib_cfg.motion_file` / `object_motion_file` / `object_usd_path` slot without any conversion.
 
@@ -75,7 +92,7 @@ nvidia/PhysicalAI-Robotics-Locomanipulation-GRAIL/
     └── FoundationPose/weights/                           # object 6-DoF estimator (refiner + scorer)
 ```
 
-The 3-digit `NNN` index restarts at 0 within each `<object>`. Filenames are deterministic so that a re-export of the same source data produces the same on-disk layout.
+The 3-digit `NNN` index restarts at 0 within each `<object>`.
 
 ###  Dataset Statistics per HOI Category: