Search Results for author:
Found 3 papers, 1 papers with code
Detecting the Starting Frame of Actions in Video
In this work, we address the problem of precisely localizing key frames of an action, for example, the precise time that a pitcher releases a baseball, or the precise time that a crowd begins to applaud.
Learning Concept Embeddings with Combined Human-Machine Expertise
This paper presents our work on "SNaCK," a low-dimensional concept embedding algorithm that combines human expertise with automatic machine similarity kernels.
Cost-Effective HITs for Relative Similarity Comparisons
In this work we explore an alternative display for collecting triplets and analyze the monetary cost and speed of the display.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
