5 papers
SpeedNet: Learning the Speediness in Videos
Sagie Benaim, Ariel Ephrat, Oran Lang +5
We wish to automatically predict the "speediness" of moving objects in videos---whether they move faster, at, or slower than their "natural" speed. The core component in our approa…
Neural separation of observed and unobserved distributions
Tavi Halperin, Ariel Ephrat, Yedid Hoshen
Separating mixed distributions is a long standing challenge for machine learning and signal processing. Most current methods either rely on making strong assumptions on the source…
Dynamic Temporal Alignment of Speech to Lips
Tavi Halperin, Ariel Ephrat, Shmuel Peleg
Many speech segments in movies are re-recorded in a studio during postproduction, to compensate for poor sound quality as recorded on location. Manual alignment of the newly-record…
Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation
Ariel Ephrat, Inbar Mosseri, Oran Lang +5
We present a joint audio-visual model for isolating a single speech signal from a mixture of sounds such as other speakers and background noise. Solving this task using only audio…
Improved Speech Reconstruction from Silent Video
Ariel Ephrat, Tavi Halperin, Shmuel Peleg
Speechreading is the task of inferring phonetic information from visually observed articulatory facial movements, and is a notoriously difficult task for humans to perform. In this…