273 citations · 1.4k across the 86 of their papers we have counts for
17 papers · 1 filter
Open-vocabulary Semantic Segmentation with Frozen Vision-Language Models
Chaofan Ma, Yuhuan Yang, Yanfeng Wang +2
When trained at a sufficient scale, self-supervised learning has exhibited a notable ability to solve a wide range of visual or language understanding tasks. In this paper, we inve…
A Tri-Layer Plugin to Improve Occluded Detection
Guanqi Zhan, Weidi Xie, Andrew Zisserman
Detecting occluded objects still remains a challenge for state-of-the-art object detectors. The objective of this work is to improve the detection for such objects, and thereby imp…
Sparse in Space and Time: Audio-visual Synchronisation with Trainable Selectors
Vladimir Iashin, Weidi Xie, Esa Rahtu +1
The objective of this paper is audio-visual synchronisation of general videos 'in the wild'. For such videos, the events that may be harnessed for synchronisation cues may be spati…
Turbo Training with Token Dropout
Tengda Han, Weidi Xie, Andrew Zisserman
The objective of this paper is an efficient training method for video tasks. We make three contributions: (1) We propose Turbo training, a simple and versatile training paradigm fo…
A Simple Plugin for Transforming Images to Arbitrary Scales
Qinye Zhou, Ziyi Li, Weidi Xie +3
Existing models on super-resolution often specialized for one scale, fundamentally limiting their use in practical scenarios. In this paper, we aim to develop a general plugin that…
Motion-inductive Self-supervised Object Discovery in Videos
Shuangrui Ding, Weidi Xie, Yabo Chen +4
In this paper, we consider the task of unsupervised object discovery in videos. Previous works have shown promising results via processing optical flows to segment objects. However…
NamedMask: Distilling Segmenters from Complementary Foundation Models
Gyungin Shin, Weidi Xie, Samuel Albanie
The goal of this work is to segment and name regions of images without access to pixel-level labels during training. To tackle this task, we construct segmenters by distilling the…
Adaptive 3D Localization of 2D Freehand Ultrasound Brain Images
Pak-Hei Yeung, Moska Aliasi, Monique Haak +3
Two-dimensional (2D) freehand ultrasound is the mainstay in prenatal care and fetal growth monitoring. The task of matching corresponding cross-sectional planes in the 3D anatomy f…
CounTR: Transformer-based Generalised Visual Counting
Chang Liu, Yujie Zhong, Andrew Zisserman +1
In this paper, we consider the problem of generalised visual object counting, with the goal of developing a computational model for counting the number of objects from arbitrary se…
Transforming the Interactive Segmentation for Medical Imaging
Wentao Liu, Chaofan Ma, Yuhuan Yang +2
The goal of this paper is to interactively refine the automatic segmentation on challenging structures that fall behind human performance, either due to the scarcity of available a…
Aerial Monocular 3D Object Detection
Yue Hu, Shaoheng Fang, Weidi Xie +1
Drones equipped with cameras can significantly enhance human ability to perceive the world because of their remarkable maneuverability in 3D space. Ironically, object detection for…
Segmenting Moving Objects via an Object-Centric Layered Representation
Junyu Xie, Weidi Xie, Andrew Zisserman
The objective of this paper is a model that is able to discover, track and segment multiple moving objects in a video. We make four contributions: First, we introduce an object-cen…
ReCo: Retrieve and Co-segment for Zero-shot Transfer
Gyungin Shin, Weidi Xie, Samuel Albanie
Semantic segmentation has a broad range of applications, but its real-world impact has been significantly limited by the prohibitive annotation costs necessary to enable deployment…
Exploiting Transformation Invariance and Equivariance for Self-supervised Sound Localisation
Jinxiang Liu, Chen Ju, Weidi Xie +1
We present a simple yet effective self-supervised framework for audio-visual representation learning, to localize the sound source in videos. To understand what enables to learn us…
Temporal Alignment Networks for Long-term Video
Tengda Han, Weidi Xie, Andrew Zisserman
The objective of this paper is a temporal alignment network that ingests long term video sequences, and associated text sentences, in order to: (1) determine if a sentence is align…
Unsupervised Salient Object Detection with Spectral Cluster Voting
Gyungin Shin, Samuel Albanie, Weidi Xie
In this paper, we tackle the challenging task of unsupervised salient object detection (SOD) by leveraging spectral clustering on self-supervised features. We make the following co…
PromptDet: Towards Open-vocabulary Detection using Uncurated Images
Chengjian Feng, Yujie Zhong, Zequn Jie +5
The goal of this work is to establish a scalable pipeline for expanding an object detector towards novel/unseen categories, using zero manual annotations. To achieve that, we make…