activity
20172025
most citedDeep Audio-Visual Speech Recognition

796 citations · 2.2k across the 23 of their papers we have counts for

collaborators
Showing 2021Show all

8 papers · 1 filter

cs.CV2021

Audio-Visual Synchronisation in the wild

Honglie Chen, Weidi Xie, Triantafyllos Afouras +3

In this paper, we consider the problem of audio-visual synchronisation applied to videos `in-the-wild' (ie of general classes beyond speech). As a new task, we identify and curate…

cs.CV2021★ 14 cited

BBC-Oxford British Sign Language Dataset

Samuel Albanie, Gül Varol, Liliane Momeni +8

In this work, we introduce the BBC-Oxford British Sign Language (BOBSL) dataset, a large-scale video collection of British Sign Language (BSL). BOBSL is an extended and publicly re…

cs.CV2021★ 6 cited

Visual Keyword Spotting with Attention

K R Prajwal, Liliane Momeni, Triantafyllos Afouras +1

In this paper, we consider the task of spotting spoken keywords in silent video sequences -- also known as visual keyword spotting. To this end, we investigate Transformer-based mo…

cs.CV2021★ 3 cited

Sub-word Level Lip Reading With Visual Attention

K R Prajwal, Triantafyllos Afouras, Andrew Zisserman

The goal of this paper is to learn strong lip reading models that can recognise speech in silent videos. Most prior works deal with the open-set visual speech recognition problem b…

cs.CV2021

Aligning Subtitles in Sign Language Videos

Hannah Bull, Triantafyllos Afouras, Gül Varol +3

The goal of this work is to temporally align asynchronous subtitles in sign language videos. In particular, we focus on sign-language interpreted TV broadcast data comprising (i) a…

cs.CV2021★ 1 cited

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…

cs.CV2021★ 3 cited

Self-supervised object detection from audio-visual correspondence

Triantafyllos Afouras, Yuki M. Asano, Francois Fagan +2

We tackle the problem of learning object detectors without supervision. Differently from weakly-supervised object detection, we do not assume image-level class labels. Instead, we…

cs.CV2021★ 1 cited

Read and Attend: Temporal Localisation in Sign Language Videos

Gül Varol, Liliane Momeni, Samuel Albanie +2

The objective of this work is to annotate sign instances across a broad vocabulary in continuous sign language. We train a Transformer model to ingest a continuous signing stream a…