Update README.md

README.md

@@ -1,3 +1,83 @@
----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+language:
+- en
+tags:
+- video
+- multimodal
+- audio
+- audio-visual-localization
+size_categories:
+- 1B<n<10B
+pretty_name: AVATAR
+---
+
+# AVATAR: What’s Making That Sound Right Now? Video-centric Audio-Visual Localization
+
+**AVATAR** stands for **A**udio-**V**isual localiz**A**tion benchmark for a spatio-**T**empor**A**l pe**R**spective in video.
+
+AVATAR is a **benchmark dataset** designed to evaluate **video-centric audio-visual localization (AVL)** in **complex and dynamic real-world scenarios**.  
+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:  
+**Single-sound**, **Mixed-sound**, **Multi-entity**, and **Off-screen**.
+
+📄 [Paper (ICCV 2025)](https://hahyeon610.github.io/Video-centric_Audio_Visual_Localization/)  
+🌐 [Project Website](https://hahyeon610.github.io/Video-centric_Audio_Visual_Localization/)  
+📁 [Code & Data Viewer](https://huggingface.co/datasets/mipal/AVATAR/tree/main)
+
+---
+
+## 📦 Dataset Structure
+
+The dataset consists of the following files:
+
+| File | Description |
+|------|-------------|
+| `video.zip` | ~3.8GB of `.mp4` video clips |
+| `metadata.zip` | ~1.6GB of annotations (bounding boxes, segmentation masks, scenario tags) |
+| `vggsound_10k.txt` | List of 10,000 training video IDs from VGGSound |
+| `code/` | AVATAR benchmark evaluation code |
+
+Each annotated frame includes:
+- Visual bounding boxes and segmentation masks for sound-emitting objects
+- Audio-visual category labels aligned to the active sound source at each timestamp
+- Instance-level scenario labels (e.g., Off-screen, Mixed-sound)
+
+---
+
+## 🧪 Scenarios and Tasks
+
+AVATAR supports **fine-grained scenario-wise evaluation** of AVL models:
+
+1. **Single-sound**: One sound-emitting instance per frame
+2. **Mixed-sound**: Multiple overlapping sound sources (same or different categories)
+3. **Multi-entity**: One sounding instance among multiple visually similar ones
+4. **Off-screen**: No visible sound source within the frame
+
+🔍 You can evaluate your model using:
+- **Consensus IoU (CIoU)**
+- **AUC**
+- **Pixel-level TN% (for Off-screen)**
+
+---
+
+## 📋 Sample Instance (metadata)
+```json
+{
+  "video_id": str,
+  "frame_number": int,
+  "annotations": [
+    { // instance 1 (e.g., man)
+      "segmentation": [ // (x, y) annotated RLE format
+            [float, float], 
+            ...
+          ],
+      "bbox": [float, float, float, float], // (l, t, w, h),
+      "scenario": str, // "Single-Sound", "Mixed-Sound", "Multi-Entity", "Off-Screen"
+      "audio_visual_category": str,
+    },
+    { // instance 2 (e.g., piano)
+      ...
+    }, 
+    ...
+  ]
+}