---
license: cc-by-nc-4.0
task_categories:
- other
tags:
- 3d
- scannet
- qwen
- vit-features
- qwen-3d
pretty_name: Qwen-3D Cached ScanNet ViT Features
size_categories:
- 100GB<n<1TB
---

# Qwen-3D Cached ScanNet ViT Features

This dataset contains **precomputed Qwen2.5-VL ViT features** for ScanNet RGB frames, used by [Qwen-3D](https://huggingface.co/katefgroup/Qwen-3D) as presented in [Qwen-3D: A Generalist 3D Vision-Language Model for Spatial Understanding](https://arxiv.org/abs/2608.02980) to skip the ViT forward pass during training.

Project page: https://qwen-3d.github.io/  
Code: https://github.com/ll220/qwen3d  
Model: https://huggingface.co/katefgroup/Qwen-3D  
Paper: https://arxiv.org/abs/2608.02980  

See [docs/RUN.md](https://github.com/ll220/qwen3d/blob/main/docs/RUN.md) in the code repository for full training instructions (`CACHE_QWEN_FEATURES` / `FEATURE_DIR`).

## Contents

| Archive | Backbone | Approx. size |
| --- | --- | --- |
| `scannet_image_qwen_features_3b.tar` | Qwen2.5-VL-3B-Instruct | ~182 GiB |
| `scannet_image_qwen_features_7b.tar` | Qwen2.5-VL-7B-Instruct | ~319 GiB |

Each archive includes a backbone prefix (`3b/` or `7b/`). After extracting both into the same parent directory, features are stored as **bfloat16** tensors at:

```text
FEATURE_DIR/
  3b/<scene_id>/<frame>.pt
  7b/<scene_id>/<frame>.pt
```

Example: `FEATURE_DIR/3b/scene0051_03/140.pt`.

## Download and extract

```bash
# Download (or pass a single filename to download one archive)
hf download katefgroup/qwen3d_cached_scannet_vit_features --local-dir ./qwen3d_cached_scannet_vit_features

# Extract both archives into the same FEATURE_DIR
FEATURE_DIR="/path/to/scannet_image_qwen_features"
mkdir -p "$FEATURE_DIR"
tar -xf scannet_image_qwen_features_3b.tar -C "$FEATURE_DIR"
tar -xf scannet_image_qwen_features_7b.tar -C "$FEATURE_DIR"
```

This yields `FEATURE_DIR/3b/...` and `FEATURE_DIR/7b/...` (matching the layout used by Qwen-3D).

## Usage with Qwen-3D

Point `FEATURE_DIR` at the **parent** directory (the code resolves `3b` / `7b` from `QWEN_MODEL`):

```bash
CACHE_QWEN_FEATURES True \
FEATURE_DIR "/path/to/scannet_image_qwen_features" \
QWEN_MODEL "Qwen/Qwen2.5-VL-3B-Instruct"
```

For the 7B backbone, keep the same `FEATURE_DIR` and switch the model:

```bash
CACHE_QWEN_FEATURES True \
FEATURE_DIR "/path/to/scannet_image_qwen_features" \
QWEN_MODEL "Qwen/Qwen2.5-VL-7B-Instruct"
```

- On a cache hit, the model skips the ViT forward.
- On a miss during ScanNet training, it runs the ViT and writes missing `.pt` files under the resolved backbone subdirectory.
- Caching applies to **ScanNet datasets only**. Leave `CACHE_QWEN_FEATURES False` (default) if you are not using cached features.

To rebuild the cache yourself instead of downloading, see [`docs/cache_qwen_vit_features.py`](https://github.com/ll220/qwen3d/blob/main/docs/cache_qwen_vit_features.py).

## Citation

```bibtex
@inproceedings{lin2026qwen3d,
  title     = {Qwen-3D: A Generalist 3D Vision-Language Model for Spatial Understanding},
  author    = {Lin, Lucy and Jain, Ayush and Liu, Yifan and Fragkiadaki, Katerina},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year      = {2026}
}
```

**License Note:** This dataset is released under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). It may be used for non-commercial research purposes. Commercial use is not permitted under this license. ScanNet data itself is subject to the [ScanNet Terms of Use](http://www.scan-net.org/).