xuguohai / x-clip Goto Github PK
View Code? Open in Web Editor NEWAn official implementation for "X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval"
Home Page: https://arxiv.org/abs/2207.07285
License: MIT License
An official implementation for "X-CLIP: End-to-End Multi-grained Contrastive Learning for Video-Text Retrieval"
Home Page: https://arxiv.org/abs/2207.07285
License: MIT License
X-CLIP/modules/modeling_xclip.py
Line 327 in 6b5344f
Hi, thank you for the wonderful job!
I suppose the use of .t() in sentence-frame score , it seems that this transpose make the original [bs_text, bs_video] to [bs_video, bs_text], which make this score inconsistent with other scores. I am wondering whether my understanding is correct.
Thanks! Hope to discuss with you!
Dear Author,
I really am appreciated and fascinated by your work, and feel thankful of releasing your code.
I know that CLIP4clip + meanP have all the best performance among CLIP4Clip + seqTranf, seqLSTM, and tightTransf,
But I found that in your script, always seqTransf are recommended in sh files.
Is that any special reason that why "sim_header == seqTransf" is default setting?
I had looked your Table 2 on MSVD, your model recorded X-CLIP(ViT-B/32) R@1 scores 47.1 .
Is it mean that when X-Clip with seqTransf is the best than any other mode -meanP, tightTransf- ?
I cannot find that what kind of sim_header retrieved that scores in that table.
If X-CLIP + seqtrasnf is recommended anyway,
any special reason why seqTrasnf outperforms than meanP, unlike Clip4Clip did?
Sincerely,
Hi, thanks for your nice and open-sourced and job.
I have some questions about the experimental setup in Tab. 6.
According to my experimental results, there is an obvious decrease if only infer on Exp15's checkpoint. So, I guess all the experimental results were obtained through retraining. Hope to get your confirmation.
Due to the huge size of original dataset, I extracted images from the original videos with FPS=1, and trained the CLIP4clip(meanP) on 8 RTX3090. Due to the GPU memory constrain, I set the gradient_accumulation_steps=2.
The caption is downloaded from https://cs.stanford.edu/people/ranjaykrishna/densevid/.
I first try to reproduce the results of CLIP4clip(meanP / ViT-B/32) on ActivityNet and get R@1=37.9 which is much worse than 40.5 reported in Table 5.
Do authors have any useful experience on this issue? Thanks very much!
Hello! I was wondering if you have the final model weights after you finished training the model. I know you initialize with the CLIP weights, but it would be super helpful to have the final model weights as well. Thank you!
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.