The objective of this work is speaker recognition under noisy and unconstrained conditions.
We make two key contributions. First, we introduce a very large-scale audio-visual dataset …

Our objective is to transform a video into a set of discrete audio-visual objects using self-
supervised learning. To this end, we introduce a model that uses attention to localize and …

Active speaker detection (ASD) seeks to detect who is speaking in a visual scene of one or
more speakers. The successful ASD depends on accurate interpretation of short-term and …

Most existing datasets for speaker identification contain samples obtained under quite
constrained conditions, and are usually hand-annotated, hence limited in size. The goal of …

Movement dataset reviews exist but are limited in coverage, both in terms of size and
research discipline. While topic-specific reviews clearly have their merit, it is critical to have a …

The goal of this work is to determine the audio-video synchronisation between mouth motion
and speech in a video. We propose a two-stream ConvNet architecture that enables the …

Active speaker detection is an important component in video analysis algorithms for
applications such as speaker diarization, video re-targeting for meetings, speech …

Active speaker detection is a challenging task in audio-visual scenarios, with the aim to
detect who is speaking in one or more speaker scenarios. This task has received …

The rapid progress of multimodal signal processing in recent years has cleared the way for
novel applications in human-computer interaction, surveillance, and telecommunication …

Active speaker detection (ASD) in videos with multiple speakers is a challenging task as it
requires learning effective audiovisual features and spatial-temporal correlations over long …