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Implementation:Open compass VLMEvalKit LongVideoBench

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Revision as of 13:29, 16 February 2026 by Admin (talk | contribs) (Auto-imported from implementations/Open_compass_VLMEvalKit_LongVideoBench.md)
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Field Value
source VLMEvalKit
domain Vision, Benchmarking, Long Video Understanding

Overview

Benchmark dataset implementation for LongVideoBench long video multiple-choice evaluation in VLMEvalKit.

Description

LongVideoBench inherits from VideoBaseDataset and implements the LongVideoBench benchmark for evaluating models on long video understanding through multiple-choice questions. The TYPE field is set to 'Video-MCQ'. It supports optional subtitle usage and downloads data from HuggingFace (longvideobench/LongVideoBench) with MD5 integrity verification.

Usage

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

Code Reference

  • Source: vlmeval/dataset/longvideobench.py, Lines: L1-332
  • Import: from vlmeval.dataset.longvideobench import LongVideoBench

Signature:

class LongVideoBench(VideoBaseDataset):
    MD5 = '82905eae3a5ae7383c5a8ee9655e1ab9'
    TYPE = 'Video-MCQ'
    DEFAULT_JUDGE = ['chatgpt-0125', 'gpt-4-0125']
    ...

I/O Contract

Direction Description
Inputs TSV dataset file with long video paths and multiple-choice questions
Outputs Evaluation results DataFrame with MCQ accuracy scores

Usage Examples

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

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