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[QA] Self-Supervised Learning of Motion Concepts by Optimizing Counterfactuals
from Arxiv Papers Hosted by Igor Melnyk
Opt-CWM is a self-supervised method for motion estimation from videos, achieving state-of-the-art performance without labeled data by optimizing counterfactual probes from a pre-trained model. https://arxiv.org/abs//2503.19953 YouTube: https://www.youtube.com/@ArxivPapers TikTok: https://www.tiktok.com/@arxiv_papers Apple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016 Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers
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This episode was published on March 27, 2025.
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