Closed 921112343 closed 4 months ago
Hi~ Thanks for your interest. I will give a scripts for EgoSchema later~
@921112343 Please check https://github.com/OpenGVLab/Ask-Anything/blob/main/video_chat2/demo/demo_mistral.ipynb
Very wonderful update !! Could you please also offer some examples for evaluating zero-shot videoqa, like msvd and msrvtt....thanks a lot !
For the VideoQA, you can simply modify the code and save the responses, and then use ChatGPT to give a score.
However, I don't suggest to evaluate the VideoLMMs' capacities on the tradictional QA benchmarks like MSRVTT/MSVD, which can not reveal their essential problems.
Thank you for your reply, I was wondering if any new work has been done recently to discuss this metric like MSRVTT/MSVD....cause your view is very new to me...
@921112343 Please check https://github.com/OpenGVLab/Ask-Anything/blob/main/video_chat2/demo/demo_mistral.ipynb
Thanks for your update!!
Thank you for your reply, I was wondering if any new work has been done recently to discuss this metric like MSRVTT/MSVD....cause your view is very new to me...
No work discuss the potential bias in such benchmark, but one paper has reveled the single frame bias
about the video dataset. Please check Revealing Single Frame Bias for Video-and-Language Learning
.
Thank you for open-sourcing this excellent work. I have noticed that your model performs exceptionally well on the EgoSchema dataset. However, I found detailed descriptions of your evaluation process only for NExT-QA, STAR, and TVQA in the Readme. Could you please share the steps you took to prepare the EgoSchema data and how you evaluated your model on it?