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Found 11 papers, 6 papers with code
Lumiere: A Space-Time Diffusion Model for Video Generation
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 synthesis.
Ranked #6 on
Text-to-Video Generation
on UCF-101
Teaching CLIP to Count to Ten
Our counting loss is deployed over automatically-created counterfactual examples, each consisting of an image and a caption containing an incorrect object count.
SpeedNet: Learning the Speediness in Videos
We demonstrate how those learned features can boost the performance of self-supervised action recognition, and can be used for video retrieval.
Neural separation of observed and unobserved distributions
In this work, we introduce a new method---Neural Egg Separation---to tackle the scenario of extracting a signal from an unobserved distribution additively mixed with a signal from an observed distribution.
Neural Separation of Observed and Unobserved Distribution
In this work, we introduce a new method---Neural Egg Separation---to tackle the scenario of extracting a signal from an unobserved distribution additively mixed with a signal from an observed distribution.
Dynamic Temporal Alignment of Speech to Lips
This alignment is based on deep audio-visual features, mapping the lips video and the speech signal to a shared representation.
Looking to Listen at the Cocktail Party: A Speaker-Independent Audio-Visual Model for Speech Separation
Solving this task using only audio as input is extremely challenging and does not provide an association of the separated speech signals with speakers in the video.
Seeing Through Noise: Visually Driven Speaker Separation and Enhancement
Isolating the voice of a specific person while filtering out other voices or background noises is challenging when video is shot in noisy environments.
Improved Speech Reconstruction from Silent Video
Speechreading is the task of inferring phonetic information from visually observed articulatory facial movements, and is a notoriously difficult task for humans to perform.
Vid2speech: Speech Reconstruction from Silent Video
Speechreading is a notoriously difficult task for humans to perform.
Compact CNN for Indexing Egocentric Videos
Furthermore, our CNN is able to recognize whether a video is egocentric or not with 99. 2% accuracy, up by 24% from current state-of-the-art.
