75.5k citations · 100.8k across the 160 of their papers we have counts for
32 papers · 1 filter
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…
Persistent Animal Identification Leveraging Non-Visual Markers
Michael P. J. Camilleri, Li Zhang, Rasneer S. Bains +2
Our objective is to locate and provide a unique identifier for each mouse in a cluttered home-cage environment through time, as a precursor to automated behaviour recognition for b…
Label, Verify, Correct: A Simple Few Shot Object Detection Method
Prannay Kaul, Weidi Xie, Andrew Zisserman
The objective of this paper is few-shot object detection (FSOD) -- the task of expanding an object detector for a new category given only a few instances for training. We introduce…
Input-level Inductive Biases for 3D Reconstruction
Wang Yifan, Carl Doersch, Relja Arandjelović +2
Much of the recent progress in 3D vision has been driven by the development of specialized architectures that incorporate geometrical inductive biases. In this paper we tackle 3D r…
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…
It's About Time: Analog Clock Reading in the Wild
Charig Yang, Weidi Xie, Andrew Zisserman
In this paper, we present a framework for reading analog clocks in natural images or videos. Specifically, we make the following contributions: First, we create a scalable pipeline…
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…
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…
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…
Open-Set Recognition: a Good Closed-Set Classifier is All You Need?
Sagar Vaze, Kai Han, Andrea Vedaldi +1
The ability to identify whether or not a test sample belongs to one of the semantic classes in a classifier's training set is critical to practical deployment of the model. This ta…
PASS: An ImageNet replacement for self-supervised pretraining without humans
Yuki M. Asano, Christian Rupprecht, Andrew Zisserman +1
Computer vision has long relied on ImageNet and other large datasets of images sampled from the Internet for pretraining models. However, these datasets have ethical and technical…
Self-Supervised Multi-Modal Alignment for Whole Body Medical Imaging
Rhydian Windsor, Amir Jamaludin, Timor Kadir +1
This paper explores the use of self-supervised deep learning in medical imaging in cases where two scan modalities are available for the same subject. Specifically, we use a large…
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac +12
A central goal of machine learning is the development of systems that can solve many problems in as many data domains as possible. Current architectures, however, cannot be applied…
AutoNovel: Automatically Discovering and Learning Novel Visual Categories
Kai Han, Sylvestre-Alvise Rebuffi, Sébastien Ehrhardt +2
We tackle the problem of discovering novel classes in an image collection given labelled examples of other classes. We present a new approach called AutoNovel to address this probl…
NeRF in detail: Learning to sample for view synthesis
Relja Arandjelović, Andrew Zisserman
Neural radiance fields (NeRF) methods have demonstrated impressive novel view synthesis performance. The core approach is to render individual rays by querying a neural network at…
Comment on Stochastic Polyak Step-Size: Performance of ALI-G
Leonard Berrada, Andrew Zisserman, M. Pawan Kumar
This is a short note on the performance of the ALI-G algorithm (Berrada et al., 2020) as reported in (Loizou et al., 2021). ALI-G (Berrada et al., 2020) and SPS (Loizou et al., 202…
Face, Body, Voice: Video Person-Clustering with Multiple Modalities
Andrew Brown, Vicky Kalogeiton, Andrew Zisserman
The objective of this work is person-clustering in videos -- grouping characters according to their identity. Previous methods focus on the narrower task of face-clustering, and fo…
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…
Omnimatte: Associating Objects and Their Effects in Video
Erika Lu, Forrester Cole, Tali Dekel +3
Computer vision is increasingly effective at segmenting objects in images and videos; however, scene effects related to the objects -- shadows, reflections, generated smoke, etc --…
Temporal Query Networks for Fine-grained Video Understanding
Chuhan Zhang, Ankush Gupta, Andrew Zisserman
Our objective in this work is fine-grained classification of actions in untrimmed videos, where the actions may be temporally extended or may span only a few frames of the video. W…
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…
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations
Debidatta Dwibedi, Yusuf Aytar, Jonathan Tompson +2
Self-supervised learning algorithms based on instance discrimination train encoders to be invariant to pre-defined transformations of the same instance. While most methods treat di…
TEACHTEXT: CrossModal Generalized Distillation for Text-Video Retrieval
Ioana Croitoru, Simion-Vlad Bogolin, Marius Leordeanu +4
In recent years, considerable progress on the task of text-video retrieval has been achieved by leveraging large-scale pretraining on visual and audio datasets to construct powerfu…
Self-supervised Video Object Segmentation by Motion Grouping
Charig Yang, Hala Lamdouar, Erika Lu +2
Animals have evolved highly functional visual systems to understand motion, assisting perception even under complex environments. In this paper, we work towards developing a comput…