587 citations · 691 across the 9 of their papers we have counts for
12 papers
TokenVerse: Versatile Multi-concept Personalization in Token Modulation Space
Daniel Garibi, Shahar Yadin, Roni Paiss +6
We present TokenVerse -- a method for multi-concept personalization, leveraging a pre-trained text-to-image diffusion model. Our framework can disentangle complex visual elements a…
Still-Moving: Customized Video Generation without Customized Video Data
Hila Chefer, Shiran Zada, Roni Paiss +7
Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expan…
Lumiere: A Space-Time Diffusion Model for Video Generation
Omer Bar-Tal, Hila Chefer, Omer Tov +14
We introduce Lumiere -- a text-to-video diffusion model designed for synthesizing videos that portray realistic, diverse and coherent motion -- a pivotal challenge in video synthes…
Teaching CLIP to Count to Ten
Roni Paiss, Ariel Ephrat, Omer Tov +4
Large vision-language models (VLMs), such as CLIP, learn rich joint image-text representations, facilitating advances in numerous downstream tasks, including zero-shot classificati…
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…
Seeing Through Noise: Visually Driven Speaker Separation and Enhancement
Aviv Gabbay, Ariel Ephrat, Tavi Halperin +1
Isolating the voice of a specific person while filtering out other voices or background noises is challenging when video is shot in noisy environments. We propose audio-visual meth…
Vid2speech: Speech Reconstruction from Silent Video
Ariel Ephrat, Shmuel Peleg
Speechreading is a notoriously difficult task for humans to perform. In this paper we present an end-to-end model based on a convolutional neural network (CNN) for generating an in…
Compact CNN for Indexing Egocentric Videos
Yair Poleg, Ariel Ephrat, Shmuel Peleg +1
While egocentric video is becoming increasingly popular, browsing it is very difficult. In this paper we present a compact 3D Convolutional Neural Network (CNN) architecture for lo…