| | --- |
| | language: |
| | - en |
| | tags: |
| | - 3d |
| | - multi-view |
| | - vision-language |
| | - scanrefer |
| | pretty_name: MVRefer |
| | --- |
| | |
| | # MVRefer Dataset |
| |
|
| | ## 1. Dataset Overview |
| | **MVRefer** is the first benchmark dataset specifically designed for the **Multi-view 3D Referring Expression Segmentation (MV-3DRES)** task. It is built to align 3D language grounding with the realistic sensing conditions of embodied agents, which typically perceive environments through only a few casually captured RGB views rather than idealized dense point clouds. |
| |
|
| | ## 2. Dataset Construction & Features |
| | The MVRefer benchmark is constructed based on ScanRefer and ScanNet sequences: |
| | * **Sparse Multi-view Sampling**: For each language-object pair in ScanRefer, we sample N=8 RGB frames from the raw ScanNet video stream at uniform temporal intervals to approximate sparse, on-the-fly observations. |
| | * **Visibility Validation**: To ensure each sample remains resolvable, we perform a visibility validation step. If none of the initial eight images contain the target, we replace one no-target frame with a target-visible frame. This guarantees at least one positive view while naturally preserving a high proportion of no-target views. |
| | * **Difficulty Splits**: To evaluate robustness under varying signal sparsity, we define two difficulty splits based on the target's 2D pixel ratio: |
| | * **Hard Split**: The target occupies less than 5% of pixels in all its visible views. |
| | * **Easy Split**: At least one view contains at least 5% target pixels. |
| |
|
| | ## 3. Data Format |
| | The dataset annotations are provided in JSON format. The hierarchical structure is organized by scene, target object, and the sampled frames along with their corresponding 2D pixel ratios. |
| |
|
| | Here is an example of the data structure: |
| | ```json |
| | { |
| | "scene0011_00": { |
| | "5": { |
| | "0": 0.0, |
| | "339": 0.0, |
| | "678": 0.0, |
| | "1017": 0.0, |
| | "1356": 0.0, |
| | "1695": 0.0, |
| | "2034": 0.014394258238955208, |
| | "2373": 0.0 |
| | }, |
| | "13": { ... } |
| | } |
| | } |
| | ``` |
| | Paper Link: You can find more details in our paper on Hugging Face: www.huggingface.co/papers/2601.06874 |
