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RefCOCOg-UMD Test Partitioning

This dataset provides fine-grained evaluation splits for the RefCOCOg-UMD test set, designed for Referring Expression Comprehension (REC) tasks. Each sample is partitioned by difficulty level and referential type to enable more detailed performance analysis.

Data Structure

Each .pth file contains a list of tuples with the following structure:

import torch

data = torch.load("Easy.pth")
for item in data:
    img_name, hw_dict, bbox, phrase, obj_mask = item
    # img_name: str - Image filename
    # hw_dict: dict - Height and width info {"height": int, "width": int}
    # bbox: list - Bounding box [x1, y1, x2, y2]
    # phrase: str - Referring expression text
    # obj_mask: tensor/array - Object segmentation mask

File Organization

By Difficulty Level

  • Easy.pth - Simple referring expressions (4,109 samples)
  • Medium.pth - Moderate complexity (4,517 samples)
  • Hard.pth - Complex expressions (856 samples)

By Referential Type × Difficulty

  • {Type}_Easy.pth, {Type}_Medium.pth, {Type}_Hard.pth
  • Types: Attribute, Relation, Logic, Ambiguity, Perspective

Statistics for Each File

Filename Avg. Length Samples
Attribute_Easy.pth 35.92 3,076
Attribute_Medium.pth 48.74 3,431
Attribute_Hard.pth 50.90 563
Relation_Easy.pth 37.86 2,673
Relation_Medium.pth 47.51 4,092
Relation_Hard.pth 51.95 709
Logic_Easy.pth 49.92 172
Logic_Medium.pth 53.27 376
Logic_Hard.pth 61.68 118
Ambiguity_Easy.pth 32.35 174
Ambiguity_Medium.pth 42.62 1,659
Ambiguity_Hard.pth 45.64 783
Perspective_Easy.pth 30.07 299
Perspective_Medium.pth 44.29 955
Perspective_Hard.pth 52.14 254
Easy.pth 33.85 4,109
Medium.pth 46.19 4,517
Hard.pth 47.87 856

Statistics for Difficulty Levels and Referential Types

STATISTICS OF THE FINE-GRAINED EVALUATION SPLITS ON REFCOCOG-UMD TEST SET. EACH SAMPLE IS ASSIGNED ONE DIFFICULTY LEVEL, WHILE REFERENTIAL CATEGORIES MAY OVERLAP ACROSS SAMPLES.

Category Subset Avg. Length Samples Total
Difficulty Easy 33.85 4,109 9,482
Medium 46.19 4,517
Hard 47.87 856
Referential Type Attribute 43.33 7,070 19,334
Relation 44.48 7,474
Logic 53.89 666
Ambiguity 42.84 2,616
Perspective 42.79 1,508

Usage

from huggingface_hub import hf_hub_download
import torch

# Download a specific file
file_path = hf_hub_download(
    repo_id="marloweee/BARE_grefumd_test_partitioning",
    filename="Easy.pth",
    repo_type="dataset"
)

# Load and iterate
data = torch.load(file_path)
for img_name, hw_dict, bbox, phrase, obj_mask in data:
    print(f"Image: {img_name}, Query: {phrase}")

License

This dataset is released under the Apache 2.0 License.

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