---
pretty_name: SnapPhysics Mass Estimation Benchmark
language:
- en
tags:
- mass-estimation
- AR
- VR
- MR
- 3D reconstruction
- physical interaction
configs:
- config_name: GT_object_mass
  default: true
  data_files:
  - split: test
    path: Mass_Estimation_Result/GT_object_mass.csv
- config_name: baseline_mass_estimation
  data_files:
  - split: test
    path: Mass_Estimation_Result/baseline_mass_estimation.csv
- config_name: Snapphysics_mass_estimation
  data_files:
  - split: test
    path: Mass_Estimation_Result/Snapphysics_mass_estimation.csv
- config_name: observations
  data_files:
  - split: test
    path: observations.csv
- config_name: snapphysics_CoG_estimation
  data_files:
  - split: test
    path: snapphysics_CoG_estimation.csv
---

# SnapPhysics Mass Estimation Benchmark

This dataset provides a **mass estimation benchmark for the 50 objects evaluated
in the SnapPhysics paper**, *SnapPhysics: A Physics-Aware Scene Graph from a Single
View for Interactive Mixed Reality Scenes*. Three separate tables provide mass
ground truth, baseline estimates, and SnapPhysics estimates for the same 50
benchmark objects, with one row per object in each table. Images, masks, and
3D reconstructions are supporting assets.

## Mass data

The GT, baseline, and SnapPhysics mass result tables are grouped in
[Mass_Estimation_Result/](Mass_Estimation_Result/).

| File | Contents |
| --- | --- |
| [GT_object_mass.csv](Mass_Estimation_Result/GT_object_mass.csv) | GT masses for the 50 benchmark objects, taken from the supplied category-specific GT JSON snapshots |
| [baseline_mass_estimation.csv](Mass_Estimation_Result/baseline_mass_estimation.csv) | VLM_only, sam3d, and sam3d+sg mean mass estimates for the same 50 objects |
| [Snapphysics_mass_estimation.csv](Mass_Estimation_Result/Snapphysics_mass_estimation.csv) | SnapPhysics mean mass estimates, standard deviations, and image-specific center-of-gravity estimates for the same 50 objects |
| [snapphysics_CoG_estimation.csv](snapphysics_CoG_estimation.csv) | Center-of-gravity estimates for the 96 linked object observations, with crop and PLY references |
| [observations.csv](observations.csv) | Links from evaluation objects to observations, scenes, masks, crops, and 3D files |
| [scenes.json](scenes.json) | Scene images, object file lists, coordinate frames, and source mappings |
| [raw_estimates/](raw_estimates/) | Individual baseline and SnapPhysics repeat estimates used to compute the summaries |

All masses are in **kilograms**.
Original image identifiers are recorded in [scenes.json](scenes.json).
GT source filenames and JSON paths are recorded in the tables.

For each object observation in an input image, each method was evaluated with
**10 independent runs × 10 repetitions per run**, for **100 inference attempts**.
The estimation tables report mean mass estimates. `std_mass_kg` is the population
standard deviation across valid repeats. Individual prediction records are
provided in [raw_estimates/](raw_estimates/).

## Estimated Center of Gravity

Estimated center-of-gravity coordinates are provided in
[snapphysics_CoG_estimation.csv](snapphysics_CoG_estimation.csv), with separate
2D and 3D coordinate columns and one row per object observation.

These are **estimates, not measured ground truth**. Image coordinates are
normalized within the referenced crop; 3D coordinates use the referenced PLY's
original frame in **arbitrary units, not meters**.

For each source observation, coordinates are the arithmetic mean of ten run
summaries, each based on ten valid predictions. Stored 2D and 3D coordinates
are rounded to four and six decimal places, respectively, before averaging.
Coordinates from different observations are kept separate.

## Scenes

Images are titled **Dining room 1–5**, **Office 1–5**, **Living 1–5**, and
**Desk Item 1–3**. The object count is the number of reconstructed objects
included with each scene entry.

| Image title | Objects | Image and reconstruction files |
| --- | ---: | --- |
| Dining room 1 | 11 | [Open scene](scenes/Dining_room_1) |
| Dining room 2 | 11 | [Open scene](scenes/Dining_room_2) |
| Dining room 3 | 9 | [Open scene](scenes/Dining_room_3) |
| Dining room 4 | 9 | [Open scene](scenes/Dining_room_4) |
| Dining room 5 | 6 | [Open scene](scenes/Dining_room_5) |
| Office 1 | 5 | [Open scene](scenes/Office_1) |
| Office 2 | 7 | [Open scene](scenes/Office_2) |
| Office 3 | 7 | [Open scene](scenes/Office_3) |
| Office 4 | 2 | [Open scene](scenes/Office_4) |
| Office 5 | 4 | [Open scene](scenes/Office_5) |
| Living 1 | 3 | [Open scene](scenes/Living_1) |
| Living 2 | 4 | [Open scene](scenes/Living_2) |
| Living 3 | 4 | [Open scene](scenes/Living_3) |
| Living 4 | 4 | [Open scene](scenes/Living_4) |
| Living 5 | 3 | [Open scene](scenes/Living_5) |
| Desk Item 1 | 3 | [Open scene](scenes/Desk_Item_1) |
| Desk Item 2 | 4 | [Open scene](scenes/Desk_Item_2) |
| Desk Item 3 | 3 | [Open scene](scenes/Desk_Item_3) |

[scenes.json](scenes.json) lists the image and object file paths.

## Reconstruction files

Each scene folder contains its image and the `masks/`, `crops/`, and
`3D_objects/` subfolders.

PLY files contain Gaussian vertices and retain their original coordinates.
For entries with `asset_relationship=same_image`, load the scene's object files
together.