README.md

ViGiL3D Dataset

Please find the text descriptions and metadata for each visual grounding prompt here. The scene data can be found at the original sources:

The following files can be found here:

vigil3d_scannet.csv - visual grounding descriptions for selected ScanNet scenes
vigil3d_scannetpp.csv - visual grounding descriptions for selected ScanNet++ scenes

Each CSV includes the following fields:

prompt_id - ID of prompt (ideally, should be unique across scene datasets)
scene_id - ID of scene
object_id - IDs of target objects (as specified in ground truth object mapping)
object_name - text label of object category, if applicable
description - natural language description of target object
pair_id - integer ID representing pairs of descriptions which were designed to be similar
is_valid - 1 if a valid prompt, else 0 if it should be ignored

Additional fields (most prefixed as num_) include manual metadata characterizing the linguistic patterns of each prompt. These include

num_attributes_target - number of attributes used to describe target object(s)
num_attributes_anchors - number of attributes used to describe anchor objects
num_attribute_type_* - captures use of different attribute types (e.g. color, size, material)
num_relationships_target - number of relationships used to compare target objects with other objects
num_relationships_anchors - number of relationships used to compare anchor objects to one another
num_relationship_type_* - captures use of different relationship types (e.g. near, far, vertical)
num_coreferences - 1 if coreferences are used
num_target_not_first_np - 1 if target is first noun phrase (NP) in prompt
granularity - captures specificity of target object reference (e.g. generic, coarse-grained, fine-grained)
num_anchor_type_* - captures use of different types of anchors (e.g. single, multiple, viewpoint, agent)
num_negation - 1 if negation was used in prompt, else 0