OpenGVLab / OpenGVLab/Ask-Anything

Evaluation results on MVBench different from the paper

Open
#90 7 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
3.4k
Forks
268
PR merge metrics
No merged PRs in 30d

Description

Hi, I have tested the VideoChat2 model on my server and found that the test results are different from the paper. My results are listed as follows:
{"Action Sequence": 66.0, "Action Prediction": 47.5, "Action Antonym": 83.5, "Fine-grained Action": 49.5, "Unexpected Action": 60.0, "Object Existence": 57.99999999999999, "Object Interaction": 71.5, "Object Shuffle": 41.5, "Moving Direction": 23.0, "Action Localization": 22.5, "Scene Transition": 88.5, "Action Count": 39.5, "Moving Count": 42.0, "Moving Attribute": 58.5, "State Change": 44.0, "Fine-grained Pose": 49.0, "Character Order": 36.5, "Egocentric Navigation": 35.0, "Episodic Reasoning": 38.5, "Counterfactual Inference": 65.0, "Avg": 50.975}
The results for OS, AL, AC, ER, and CI are different. Could you help me find the reasons?

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reproducing the VideoChat2 evaluation on MVBench and comparing the listed results with the paper. Focus on the reported differences for OS, AL, AC, ER, and CI, and document the evaluation conditions and the identified reason for the mismatch as the completion criteria.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning, testing-qa
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.