| --- |
| license: mit |
| task_categories: |
| - visual-document-retrieval |
| - text-to-video |
| language: |
| - en |
| tags: |
| - video-retrieval |
| - generative-retrieval |
| - semantic-ids |
| - text-to-video |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # GRDR-TVR: Generative Recall, Dense Reranking for Text-to-Video Retrieval |
|
|
| This dataset contains the pre-extracted video features and trained model checkpoints for the GRDR (Generative Recall, Dense Reranking) framework for efficient Text-to-Video Retrieval (TVR). |
|
|
| ## 📄 Paper |
|
|
| **Generative Recall, Dense Reranking: Learning Multi-View Semantic IDs for Efficient Text-to-Video Retrieval** |
|
|
|
|
| [Paper PDF](https://arxiv.org/abs/XXXX.XXXXX) | [Code Repository](https://github.com/JasonCoderMaker/GRDR) |
|
|
| ## 📊 Dataset Overview |
|
|
| This dataset includes three main components: |
|
|
| ### 1. InternVideo2 Features (~3.4GB) |
| Pre-extracted video features using InternVideo2 encoder for four benchmark datasets: |
| - **MSR-VTT**: 10,000 videos (932MB) |
| - **ActivityNet**: 20,000 videos (1.1GB) |
| - **DiDeMo**: 10,464 videos (916MB) |
| - **LSMDC**: 1,000 movies, 118,081 clips (424MB) |
|
|
| **Feature Details:** |
| - Dimension: 512-d embeddings |
| - Format: Pickle files (`.pkl`) with `{video_id: embedding}` mappings |
| - Extraction: InternVideo2 (InternVL-2B) with temporal pooling |
|
|
| ### 2. GRDR Model Checkpoints (~2GB) |
| Trained GRDR models (T5-small based) for all four datasets: |
| - **MSR-VTT**: 494MB |
| - **ActivityNet**: 498MB |
| - **DiDeMo**: 504MB |
| - **LSMDC**: 478MB |
|
|
| **Checkpoint Components:** |
| - `best_model.pt` - Complete model checkpoint |
| - `best_model.pt.model` - T5 encoder-decoder weights |
| - `best_model.pt.videorqvae` - Video RQ-VAE quantizer |
| - `best_model.pt.code` - Pre-computed semantic IDs |
| - `best_model.pt.centroids` - Codebook centroids |
| - `best_model.pt.embedding` - Learned embeddings |
| - `best_model.pt.start_token` - Start token embeddings |
|
|
| **Model Architecture:** |
| - Base: T5-small (60M parameters) |
| - Codebook size: 128/96/200 (dataset-dependent) |
| - Max code length: 3 |
| - Training: 3-phase progressive training |
|
|
| ### 3. Xpool Reranker Checkpoints (~7.2GB) |
| Pre-trained reranker models for dense reranking stage: |
| - **MSR-VTT**: msrvtt9k_model_best.pth (1.8GB) |
| - **ActivityNet**: actnet_model_best.pth (1.8GB) |
| - **DiDeMo**: didemo_model_best.pth (1.8GB) |
| - **LSMDC**: lsmdc_model_best.pth (1.8GB) |
|
|
| ### 4. Xpool Video Features (~3.2GB) |
| Pre-extracted CLIP video features for Xpool reranker: |
| - **MSR-VTT**: 235MB |
| - **ActivityNet**: 351MB |
| - **DiDeMo**: 221MB |
| - **LSMDC**: 2.4GB |
|
|
| **Reranker Details:** |
| - Architecture: CLIP-based (ViT-B/32) |
| - Purpose: Fine-grained reranking of recalled candidates |
| - Format: PyTorch checkpoint files (`.pth`) |
|
|
| ## 📂 Repository Structure |
|
|
| ``` |
| GRDR-TVR/ |
| ├── README.md # This file |
| ├── download_features.py # Python download utility |
| ├── download_checkpoints.sh # Bash download script |
| │ |
| ├── InternVideo2/ # Video Features (3.4GB) |
| │ ├── actnet/ |
| │ │ └── actnet_internvideo2.pkl |
| │ ├── didemo/ |
| │ │ └── didemo_internvideo2.pkl |
| │ ├── lsmdc/ |
| │ │ └── lsmdc_internvideo2.pkl |
| │ └── msrvtt/ |
| │ └── msrvtt_internvideo2.pkl |
| │ |
| ├── GRDR/ # GRDR Checkpoints (2GB) |
| │ ├── actnet/best_model/ |
| │ ├── didemo/best_model/ |
| │ ├── lsmdc/best_model/ |
| │ └── msrvtt/best_model/ |
| │ |
| └── Xpool/ # Reranker Checkpoints (7.2GB) |
| ├── actnet_model_best.pth |
| ├── didemo_model_best.pth |
| ├── lsmdc_model_best.pth |
| └── msrvtt9k_model_best.pth |
| ``` |
|
|
| ## 📝 License |
|
|
| This dataset is released under the MIT License. See [LICENSE](LICENSE) for details. |
|
|
| The video datasets (MSR-VTT, ActivityNet, DiDeMo, LSMDC) are subject to their original licenses. This repository only provides pre-extracted features, not the original videos. |
|
|
| ## 🙏 Acknowledgments |
|
|
| - **InternVideo2**: We thank the authors of InternVideo2 for their excellent video encoder |
| - **Xpool**: The reranker architecture is based on X-POOL |
| - **Datasets**: MSR-VTT, ActivityNet Captions, DiDeMo, and LSMDC benchmark creators |
|
|
|
|
| **Dataset Version**: 1.0 |
| **Last Updated**: January 2026 |
| **Maintained by**: [@JasonCoderMaker](https://huggingface.co/JasonCoderMaker) |
|
|
