Comments (4)
mpc001
commented on August 20, 2024
Hello @saeu5407, we do not change the temporal resolution. Specifically, we use ResNet-18 as our visual front-end, and you can find more details about the input and output size for each layer in Table S2 on page 15 at here. Also, the temporal resolution is still the same in the conformer encoder. To summarise, whether you're referring to the front-end (ResNet-18) or back-end (conformer), the output time dimension will be the same size as the input time dimension for VSR.
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saeu5407
commented on August 20, 2024
Thank you for your answer!
Then, is there no problem with putting any length of video?
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mpc001
commented on August 20, 2024
Hi, there is no problem with putting any length of video.
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saeu5407
commented on August 20, 2024
thank you for your paper and answer
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Related Issues (20)
- A potential bug HOT 1
- About the real-time AVSR model HOT 1
- `cut_or_pad` function is wrong HOT 4
- VSR Model Training Issues HOT 1
- Re-implementation error HOT 1
- cannot import name 'eval_env' from 'torchaudio._internal.module_utils' HOT 1
- What result should be obtained under normal circumstances after preprocessing? HOT 6
- AVSpeech Dataset
- Asking for how to build the corpus for LRS2 HOT 1
- Want to train VSR model for digit recognition using grid dataset.
- test issue
- Question about training on a Chinese dataset created by myself.
- train issue
- Problems with data processing using a self-built dataset HOT 1
- Problem about training
- Whether do you perform deduplication between the LRS3 test set and AVSpeech HOT 1
- Error when training on LRS2
- Issues training VSR from scratch HOT 1
- What is the minimum gpu requirement
- Finetuning Recommendation
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