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Found 6 papers, 0 papers with code
Learning Unified Embedding for Apparel Recognition
To ease the training difficulty, a novel learning scheme is proposed by using the output from specialized models as learning targets so that L2 loss can be used instead of triplet loss.
Efficient Activity Detection in Untrimmed Video with Max-Subgraph Search
We show that this detection strategy permits an efficient branch-and-cut solution for the best-scoring---and possibly non-cubically shaped---portion of the video for a given activity classifier.
Subjects and Their Objects: Localizing Interactees for a Person-Centric View of Importance
We propose to predict the "interactee" in novel images---that is, to localize the \emph{object} of a person's action.
Inferring Analogous Attributes
The appearance of an attribute can vary considerably from class to class (e. g., a "fluffy" dog vs. a "fluffy" towel), making standard class-independent attribute models break down.
Inferring Unseen Views of People
We pose unseen view synthesis as a probabilistic tensor completion problem.
Watching Unlabeled Video Helps Learn New Human Actions from Very Few Labeled Snapshots
We propose an approach to learn action categories from static images that leverages prior observations of generic human motion to augment its training process.
