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--- |
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license: cc-by-4.0 |
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language: |
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- en |
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tags: |
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- video |
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- multimodal |
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- audio |
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- audio-visual-localization |
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size_categories: |
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- 1B<n<10B |
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pretty_name: AVATAR |
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--- |
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# AVATAR: What’s Making That Sound Right Now? Video-centric Audio-Visual Localization |
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**AVATAR** stands for **A**udio-**V**isual localiz**A**tion benchmark for a spatio-**T**empor**A**l pe**R**spective in video. |
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AVATAR is a **benchmark dataset** designed to evaluate **video-centric audio-visual localization (AVL)** in **complex and dynamic real-world scenarios**. |
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Unlike previous benchmarks that rely on static image-level annotations and assume simplified conditions, AVATAR offers **high-resolution temporal annotations** over entire videos. It supports four challenging evaluation settings: |
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**Single-sound**, **Mixed-sound**, **Multi-entity**, and **Off-screen**. |
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📄 [Paper (ICCV 2025)](https://arxiv.org/abs/2507.04667) |
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🌐 [Project Website](https://hahyeon610.github.io/Video-centric_Audio_Visual_Localization/) |
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📁 [Code & Data Viewer](https://huggingface.co/datasets/mipal/AVATAR/tree/main) |
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--- |
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## 📦 Dataset Structure |
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The dataset consists of the following files: |
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| File | Description | |
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|------|-------------| |
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| `video.zip` | ~3.8GB of `.mp4` video clips | |
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| `metadata.zip` | ~1.6GB of annotations (bounding boxes, segmentation masks, scenario tags) | |
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| `vggsound_10k.txt` | List of 10,000 training video IDs from [VGGSound](https://huggingface.co/datasets/Loie/VGGSound)| |
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| `code/` | AVATAR benchmark evaluation code | |
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Each annotated frame includes: |
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- Visual bounding boxes and segmentation masks for sound-emitting objects |
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- Audio-visual category labels aligned to the active sound source at each timestamp |
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- Instance-level scenario labels (e.g., Off-screen, Mixed-sound) |
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--- |
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## 📊 Dataset Statistics |
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AVATAR provides detailed quantitative statistics to help users understand its scale and diversity. |
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| Type | Count | |
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|------------|--------| |
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| Videos | 5,000 | |
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| Frames | 24,266 | |
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| Off-screen | 670 | |
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| Scenario Type | Instances | |
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|-----------------|-----------| |
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| Total | 28,516 | |
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| Single-sound | 15,372 | |
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| Multi-entity | 9,322 | |
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| Mixed-sound | 3,822 | |
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--- |
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## 🧪 Scenarios and Tasks |
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AVATAR supports **fine-grained scenario-wise evaluation** of AVL models: |
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1. **Single-sound**: One sound-emitting instance per frame |
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2. **Mixed-sound**: Multiple overlapping sound sources (same or different categories) |
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3. **Multi-entity**: One sounding instance among multiple visually similar ones |
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4. **Off-screen**: No visible sound source within the frame |
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🔍 You can evaluate your model using: |
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- **Consensus IoU (CIoU)** |
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- **AUC** |
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- **Pixel-level TN% (for Off-screen)** |
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--- |
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## 🧩 Audio-Visual Category Diversity |
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AVATAR spans **80 audio-visual categories** covering a wide range of everyday domains, including: |
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- **Human activities** (e.g., talking, singing) |
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- **Music performances** (e.g., violin, drum, piano) |
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- **Animal sounds** (e.g., dog barking, bird chirping) |
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- **Vehicles** (e.g., car engine, helicopter) |
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- **Tools and machines** (e.g., chainsaw, blender) |
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Such diversity enables a **comprehensive evaluation** of model generalizability across varied audio-visual contexts. |
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--- |
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## 📝 Example Metadata Format |
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```json |
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{ |
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"video_id": str, |
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"frame_number": int, |
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"annotations": [ |
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{ // instance 1 (e.g., man) |
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"segmentation": [ // (x, y) annotated RLE format |
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[float, float], |
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... |
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], |
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"bbox": [float, float, float, float], // (l, t, w, h), |
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"scenario": str, // "Single-sound", "Mixed-sound", "Multi-entity", "Off-screen" |
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"audio_visual_category": str, |
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}, |
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{ // instance 2 (e.g., piano) |
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... |
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}, |
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... |
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] |
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} |
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``` |
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--- |
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## 📚 Citation |
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```bibtex |
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@InProceedings{Choi_2025_ICCV, |
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author = {Choi, Hahyeon and Lee, Junhoo and Kwak, Nojun}, |
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title = {What's Making That Sound Right Now? Video-centric Audio-Visual Localization}, |
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booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, |
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month = {October}, |
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year = {2025}, |
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pages = {20095-20104} |
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} |
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``` |
