nandakrishnan1311/ViD-GAN-Encoder

ViD-GAN Encoder (VideoRAG Retrieval Model)

ViD-GAN is a custom-trained retrieval model designed for video-based question answering using a multimodal retrieval approach.

This repository contains:

• ViD-GAN Encoder (SentenceTransformer-based)
• ViD-GAN Discriminator (grounding verification module)

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🚀 What This Model Does

ViD-GAN Encoder generates embeddings for:

• user questions
• video transcript chunks
• multimodal chunks (transcript + detected visual objects)

It is trained using contrastive learning (InfoNCE) to improve retrieval quality.

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🛠️ How to Use

Load Encoder

from sentence_transformers import SentenceTransformer
model = SentenceTransformer('nandakrishnan1311/ViD-GAN-Encoder')

Encode Text

emb = model.encode('In the UK, what is totally illegal?')
print(emb.shape)

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📦 Files

• ViD-GAN-Encoder/ : SentenceTransformer encoder
• ViD-GAN-Discriminator.pt : grounding discriminator

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⚠️ Limitations

• Trained on a small auto-generated dataset
• Visual info is based on YOLO object labels (may include false detections)
• Intended for research and prototype use

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👤 Author

Developed by Nandakrishnan O 🇮🇳