Update README.md

README.md

@@ -130,6 +130,39 @@ trainset/
 
 ```
 
+
+## Data Format Details
+
+### File Overview
+| File | Type | Shape | Description |
+|------|------|-------|-------------|
+| `audio.wav` | Audio | (N_samples,) | Original audio waveform|
+| `cam.npy` | Parameters | (N_frames, 3) | Camera parameters (position/scale) |
+| `detailcode.npy` | Parameters | (N_frames, 128) | Facial detail codes (wrinkles, fine features) |
+| `envelope.npy` | Parameters | (N_audio_samples,) | Audio envelope/amplitude over time |
+| `expcode.npy` | Parameters | (N_frames, 50) | FLAME expression parameters (50-dim) |
+| `lightcode.npy` | Parameters | (N_frames, 9, 3) | Spherical harmonics lighting (9 bands × RGB) |
+| `metadata.pkl` | Metadata | N/A | Sequence metadata (integer or dict) |
+| `posecode.npy` | Parameters | (N_frames, 6) | 3 head pose + 3 jaw pose |
+| `refimg.npy` | Image | (3, 224, 224) | Reference image (RGB, 224×224 pixels) |
+| `shapecode.npy` | Parameters | (N_frames, 100) | FLAME shape parameters (100-dim) |
+| `texcode.npy` | Parameters | (N_frames, 50) | Texture codes (50-dim) |
+
+### Coordinate Systems and Conventions
+- **FLAME model**: 3D Morphable Face Model with 5023 vertices
+- **Expression space**: 50-dimensional linear basis
+- **Shape space**: 100-dimensional PCA space
+- **Pose representation**: 3 head pose + 3 jaw pose
+- **Lighting**: 2nd-order spherical harmonics (9 bands)
+
+### Temporal Synchronization
+- **Video frames**: 25 FPS (frames per second)
+- **Audio samples**: 16,000 samples per second
+- All video parameters (`expcode`, `shapecode`, `detailcode`, `posecode`, `cam`, `lightcode`, `texcode`) share the same `N_frames` dimension
+- Audio and video are temporally aligned (frame 0 corresponds to start of audio)
+
+
+
 ### Data Statistics
 
 The dataset comprises **11,706** total video samples, spanning approximately **67.4 hours** of self-talking footage. The data is categorized by environment (Lab vs. Wild) and includes varying resolutions and subject diversity.
@@ -180,3 +213,31 @@ Raw videos from the wild (e.g., VoxCeleb2, Celebv-HQ) often contain background n
 - **HDTF:** https://huggingface.co/datasets/global-optima-research/HDTF
 - **Celebv-HQ:** https://github.com/CelebV-HQ/CelebV-HQ/
 
+## Citation
+
+If you use this dataset, please cite the original source datasets:
+
+- **GRID**: Cooke, M., et al. (2006). An audio-visual corpus for speech perception and automatic speech recognition.
+- **RAVDESS**: Livingstone, S. R., & Russo, F. A. (2018). The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS).
+- **MEAD**: Wang, K., et al. (2020). MEAD: A Large-scale Audio-visual Dataset for Emotional Talking-face Generation.
+- **VoxCeleb2**: Chung, J. S., et al. (2018). VoxCeleb2: Deep Speaker Recognition.
+- **HDTF**: Zhang, Z., et al. (2021). Flow-guided One-shot Talking Face Generation with a High-resolution Audio-visual Dataset.
+- **CelebV-HQ**: Zhu, H., et al. (2022). CelebV-HQ: A Large-Scale Video Facial Attributes Dataset.
+
+And the EMOCA model used for parameter extraction:
+- **EMOCA**: Danecek, R., et al. (2022). EMOCA: Emotion Driven Monocular Face Capture and Animation.
+
+## License
+
+Please refer to the original dataset licenses:
+- GRID: Research use only
+- RAVDESS: CC BY-NA-SC 4.0
+- MEAD, VoxCeleb2, HDTF, CelebV-HQ: Check respective dataset licenses
+
+## Notes
+
+- Not all sequence numbers are contiguous (some sequences may be missing due to quality filtering or processing failures)
+- File counts per sequence are consistent (11 files per sequence)
+- This is a processed/derived dataset - original videos are not included, only extracted parameters
+
+