MetalFabric/clothFabric/clothWoodPlastic - opaquePaper/tissue

Added: March 29, 2013, 11:02 p.m.

FOV: 58.664° (larger dimension)

Focal length: 1.340 × height

Scene: bedroom

Scene correct: True

Whitebalanced: True

Scene label correct votes:


Scene label correct score:


Whitebalance votes:


Whitebalance score:


Flickr user: salvadonica

Flickr ID: 4542667569

License: Attribution 2.0 Generic (Credit: Salvadonica Borgo del Chianti)

Material segmentations

Users were asked to draw around regions of a single type of material.

Vanishing points

Each color corresponds to one vanishing point. Hover over the points on the right to see the full lines.

Whitebalance points

Users were asked to click on points that are white or gray.

Each color corresponds to one user.

Median chroma
  • 3.998 (16.1 s)
  • 3.038 (7.74 s)
  • 6.373 (6.12 s)
  • 13.459 (4.71 s)
  • 8.481 (3.05 s)

Human reflectance judgements

Our user interface for collecting annotations shows the user an image and asks them, for a particular pair of pixels (indicated with crosshairs and labeled Points 1 and 2), which of the two points has a darker surface color. The user can then select one of three options: Point 1, Point 2, and About the same. We ask users to specify their confidence in their assessment as Guessing, Probably, or Definitely, as was done by [Branson et al. 2010].

We aggregate judgements from 5 users for each pair of points and use the CUBAM machine learning model [Welinder et al. 2010] to model two forms of bias.

See our publication for more details.

Our user interface

Point separation: 0.03

Point separation: 0.07

Intrinsic image decompositions

The input image is decomposed into a "reflectance" and "shading" layer. Note that the reflectance layer is listed twice: color (left) and grayscale (center). Decompositions are ordered by error and then runtime (best on top). The parameters for each algorithm are the same for all photos; they are set to the values that produce lowest mean error (WHDR) for all photos. See our publication for more details.

  • Algorithm: bell2014_densecrf