📄 Check out the paper: arxiv.org/pdf/2412.05275
🎥 For more results: motionflow-diffusion.github.io
We’d love to hear your thoughts or questions.
Stay tuned for more from our team! 🚀
📊 How does it compare? MotionFlow outperforms state-of-the-art methods like DMT, VMC, and others by balancing:
✅ Motion Fidelity (realistic motion)
✅ Temporal Consistency (smooth transitions)
✅ Text Alignment (prompt accuracy)
🧠 Core innovation? Instead of extensive training or fine-tuning, we extract motion dynamics from attention maps during test time.
This ensures:
✅ Fidelity to original motion
✅ Freedom to edit scene layout
MotionFlow is a novel invert-then-generate framework that uses cross-attention maps to transfer motion dynamics across contexts. It maintains motion fidelity while enabling scene edits. No extra training needed.
🌟 Exciting news! Our research, MotionFlow, is out! 🚀
A training-free method for motion transfer using pre-trained video diffusion models. 🎥✨
Big thanks to Hidir Yesiltepe, Connor Dunlop, and my advisor Pinar Yanardag. More from our lab soon—stay tuned! 🧵👇
Thanks for the answer. I was expecting to hear a similar use case.
bsky.app/profile/tmer...
I am asking this because I hear a lot of people trying to get into the first page of this list so hard. Can anyone elaborate what is the benefit of getting there?
I am curious If there is anyone who reads papers from the arxiv recent papers lists. Like directly from this link: arxiv.org/list/cs/recent
I don't. But who does? Really
Thanks to all for following me. I think I somehow got into some of the starter packs. I am normally not too active on these sites but I will try to be 🙌
The worst part was that the paper was about "fonts". Vikas handled the situation quite well 😅
This one is more comprehensive go.bsky.app/Pxcnfu6
Found this one. bsky.app/profile/sedi...
cool pack, thank you 🙌
Is there any starter pack for Vision GenAI people?
