U tweetove putem weba ili aplikacija drugih proizvođača možete dodati podatke o lokaciji, kao što su grad ili točna lokacija. Povijest lokacija tweetova uvijek možete izbrisati. Saznajte više
TCC discovers the phases of an action without additional labels. In this video, we retrieve nearest neighbors in the embedding space to frames in the reference video. In spite of many variations, TCC maps semantically similar frames to nearby points in the embedding space.pic.twitter.com/k4o4y4o6gE
Self-supervised methods are quite useful in the few-shot setting. Consider the action phase classification task. With only 1 labeled video TCC achieves similar performance to vanilla supervised learning models trained with ~50 videos.pic.twitter.com/Xu26Tpr68y
Some applications of the per-frame embeddings learned using TCC: 1. Unsupervised video alignmentpic.twitter.com/bAMpiOIRwd
This is joint work with @yusufaytar , Jonathan Tompson, @psermanet and Andrew Zisserman.
Twitter je možda preopterećen ili ima kratkotrajnih poteškoća u radu. Pokušajte ponovno ili potražite dodatne informacije u odjeljku Status Twittera.
