96 citations · 247 across the 12 of their papers we have counts for
28 papers
AVATAR submission to the Ego4D AV Transcription Challenge
Paul Hongsuck Seo, Arsha Nagrani, Cordelia Schmid
In this report, we describe our submission to the Ego4D AudioVisual (AV) Speech Transcription Challenge 2022. Our pipeline is based on AVATAR, a state of the art encoder-decoder mo…
Learning Audio-Video Modalities from Image Captions
Arsha Nagrani, Paul Hongsuck Seo, Bryan Seybold +4
A major challenge in text-video and text-audio retrieval is the lack of large-scale training data. This is unlike image-captioning, where datasets are in the order of millions of s…
Masking Modalities for Cross-modal Video Retrieval
Valentin Gabeur, Arsha Nagrani, Chen Sun +2
Pre-training on large scale unlabelled datasets has shown impressive performance improvements in the fields of computer vision and natural language processing. Given the advent of…
With a Little Help from my Temporal Context: Multimodal Egocentric Action Recognition
Evangelos Kazakos, Jaesung Huh, Arsha Nagrani +2
In egocentric videos, actions occur in quick succession. We capitalise on the action's temporal context and propose a method that learns to attend to surrounding actions in order t…
Localizing Visual Sounds the Hard Way
Honglie Chen, Weidi Xie, Triantafyllos Afouras +3
The objective of this work is to localize sound sources that are visible in a video without using manual annotations. Our key technical contribution is to show that, by training th…
Composable Augmentation Encoding for Video Representation Learning
Chen Sun, Arsha Nagrani, Yonglong Tian +1
We focus on contrastive methods for self-supervised video representation learning. A common paradigm in contrastive learning is to construct positive pairs by sampling different da…