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08/25/2023
An investigation into the impact of deep learning model choice on sex and race bias in cardiac MR segmentation
In medical imaging, artificial intelligence (AI) is increasingly being u...
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08/09/2023
SegMatch: A semi-supervised learning method for surgical instrument segmentation
Surgical instrument segmentation is recognised as a key enabler to provi...
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07/25/2023
When Multi-Task Learning Meets Partial Supervision: A Computer Vision Review
Multi-Task Learning (MTL) aims to learn multiple tasks simultaneously wh...
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07/12/2023
TreeFormer: a Semi-Supervised Transformer-based Framework for Tree Counting from a Single High Resolution Image
Automatic tree density estimation and counting using single aerial and s...
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06/20/2023
Automated Grading and Feedback Tools for Programming Education: A Systematic Review
We conducted a systematic literature review on automated grading and fee...
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06/15/2023
Text Promptable Surgical Instrument Segmentation with Vision-Language Models
In this paper, we propose a novel text promptable surgical instrument se...
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06/14/2023
LoSh: Long-Short Text Joint Prediction Network for Referring Video Object Segmentation
Referring video object segmentation (RVOS) aims to segment the target in...
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03/28/2023
HiLo: Exploiting High Low Frequency Relations for Unbiased Panoptic Scene Graph Generation
Panoptic Scene Graph generation (PSG) is a recently proposed task in ima...
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12/05/2022
Domain-general Crowd Counting in Unseen Scenarios
Domain shift across crowd data severely hinders crowd counting models to...
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12/04/2022
Exploring and Eliciting Needs and Preferences from Editors for Wikidata Recommendations
Wikidata is an open knowledge graph created, managed, and maintained col...
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11/18/2022
α DARTS Once More: Enhancing Differentiable Architecture Search by Masked Image Modeling
Differentiable architecture search (DARTS) has been a mainstream directi...
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10/27/2022
Video-based Remote Physiological Measurement via Self-supervised Learning
Video-based remote physiological measurement aims to estimate remote pho...
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09/04/2022
A systematic study of race and sex bias in CNN-based cardiac MR segmentation
In computer vision there has been significant research interest in asses...
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08/04/2022
Redesigning Multi-Scale Neural Network for Crowd Counting
Perspective distortions and crowd variations make crowd counting a chall...
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07/18/2022
Enhancing Space-time Video Super-resolution via Spatial-temporal Feature Interaction
The target of space-time video super-resolution (STVSR) is to increase b...
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07/12/2022
Dam reservoir extraction from remote sensing imagery using tailored metric learning strategies
Dam reservoirs play an important role in meeting sustainable development...
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07/08/2022
Boosting Zero-shot Learning via Contrastive Optimization of Attribute Representations
Zero-shot learning (ZSL) aims to recognize classes that do not have samp...
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03/28/2022
Learning to Prompt for Open-Vocabulary Object Detection with Vision-Language Model
Recently, vision-language pre-training shows great potential in open-voc...
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10/30/2021
MFNet: Multi-class Few-shot Segmentation Network with Pixel-wise Metric Learning
In visual recognition tasks, few-shot learning requires the ability to l...
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07/13/2021
Learning to Recommend Items to Wikidata Editors
Wikidata is an open knowledge graph built by a global community of volun...
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11/10/2020
Detecting Human-Object Interaction with Mixed Supervision
Human object interaction (HOI) detection is an important task in image u...
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11/09/2020
Fast Fourier Intrinsic Network
We address the problem of decomposing an image into albedo and shading. ...
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10/22/2020
Restoring Negative Information in Few-Shot Object Detection
Few-shot learning has recently emerged as a new challenge in the deep le...
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08/12/2020
Towards Unsupervised Crowd Counting via Regression-Detection Bi-knowledge Transfer
Unsupervised crowd counting is a challenging yet not largely explored ta...
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08/12/2020
Defending Adversarial Examples via DNN Bottleneck Reinforcement
This paper presents a DNN bottleneck reinforcement scheme to alleviate t...
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07/13/2020
Active Crowd Counting with Limited Supervision
To learn a reliable people counter from crowd images, head center annota...
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12/01/2019
Training Object Detectors from Few Weakly-Labeled and Many Unlabeled Images
Weakly-supervised object detection attempts to limit the amount of super...
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04/02/2019
Point in, Box out: Beyond Counting Persons in Crowds
Modern crowd counting methods usually employ deep neural networks (DNN) ...
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07/05/2018
Perspective-Aware CNN For Crowd Counting
Crowd counting is the task of estimating pedestrian numbers in crowd ima...
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11/13/2017
Crowd counting via scale-adaptive convolutional neural network
The task of crowd counting is to automatically estimate the pedestrian n...
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03/23/2017
Weakly Supervised Object Localization Using Things and Stuff Transfer
We propose to help weakly supervised object localization for classes whe...
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08/15/2016