Update README.md

README.md

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 - en
 ---
 
-Trained Autoencoder on WAN2.1 for 1080p and 4K videos with language guidance Quntization
+# Pyramidal Spectrum  
+### Frequency-based Hierarchically Vector Quantized VAE for Videos  
+**Official Implementation — WACV 2026**
+
+This repository provides the **official implementation** of the paper:
+
+**Pyramidal Spectrum: Frequency-based Hierarchically Vector Quantized VAE for Videos**  
+*Accepted at WACV 2026*
+
+We introduce a **new autoencoder trained on 4K-resolution video data**, featuring a **hierarchical frequency-based vector quantization** method.  
+The model leverages a **pyramidal spectral representation** to produce high-fidelity video reconstructions with an efficient latent structure.
+
+---
+
+## 📦 Installation
+
+This implementation requires installing Diffusers from the custom branch:
+
+```bash
+pip install git+https://github.com/Onkarsus13/diffusers@MMVQVae
+```
+## 🚀 Features
+- Novel **hierarchical frequency-domain quantization**  
+- Trained on **4K-resolution** video datasets  
+- Multi-level **pyramidal spectral decomposition**  
+- Highly efficient latent video representation  
+- High-quality reconstructions suitable for generative pipelines
+
+---
+
+
+```
+@inproceedings{pyramidal_spectrum_wacv2026,
+  title     = {Pyramidal Spectrum: Frequency-based Hierarchically Vector Quantized VAE for Videos},
+  author    = {Tushar, Prakash and Onkar, Susladkar and Inderjit, 
+              Inderjit Dhillon and Sparsh Mittal},
+  booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
+  year      = {2026}
+}
+```
+
+
+
+
+
+
+