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Implementation:Open compass VLMEvalKit VDC

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Revision as of 13:32, 16 February 2026 by Admin (talk | contribs) (Auto-imported from implementations/Open_compass_VLMEvalKit_VDC.md)
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Field Value
source VLMEvalKit
domain Vision, Benchmarking, Video Description, Captioning

Overview

Benchmark dataset implementation for VDC (Video Detailed Captioning) evaluation in VLMEvalKit.

Description

VDC inherits from VideoBaseDataset and implements the VDC benchmark for evaluating video detailed captioning capabilities. The TYPE field is set to 'Video-VQA'. It supports multiple subset modes including 'all', 'breakpoint', 'short', and 'detailed' caption types, with configurable data limits for subsampling.

Usage

Registered in vlmeval/dataset/__init__.py and invoked through build_dataset() by benchmark name.

Code Reference

  • Source: vlmeval/dataset/vdc.py, Lines: L1-425
  • Import: from vlmeval.dataset.vdc import VDC

Signature:

class VDC(VideoBaseDataset):
    TYPE = 'Video-VQA'
    MD5 = ''
    ...

I/O Contract

Direction Description
Inputs TSV dataset file with video paths and captioning tasks
Outputs Evaluation results DataFrame with captioning quality scores

Usage Examples

from vlmeval.dataset import build_dataset
dataset = build_dataset('VDC')

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Principle
Implementation
Heuristic
Environment