Search Results for author: Angelica I Aviles-Rivero

Found 13 papers, 2 papers with code

Contrastive Registration for Unsupervised Medical Image Segmentation

1 code implementation17 Nov 2020 Lihao Liu, Angelica I Aviles-Rivero, Carola-Bibiane Schönlieb

Secondly, we embed a contrastive learning mechanism into the registration architecture to enhance the discriminating capacity of the network in the feature-level.

Contrastive Learning Image Segmentation +3

TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation

no code implementations17 Nov 2022 Zhongying Deng, Yanqi Chen, Lihao Liu, Shujun Wang, Rihuan Ke, Carola-Bibiane Schonlieb, Angelica I Aviles-Rivero

Firstly, TrafficCAM provides both pixel-level and instance-level semantic labelling along with a large range of types of vehicles and pedestrians.

Instance Segmentation Management +1

NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning

1 code implementation17 Nov 2022 Zhongying Deng, Rihuan Ke, Carola-Bibiane Schonlieb, Angelica I Aviles-Rivero

Semi-Supervised Learning (SSL) aims to learn a model using a tiny labeled set and massive amounts of unlabeled data.

HGIB: Prognosis for Alzheimer's Disease via Hypergraph Information Bottleneck

no code implementations18 Mar 2023 Shujun Wang, Angelica I Aviles-Rivero, Zoe Kourtzi, Carola-Bibiane Schönlieb

We demonstrate, through extensive experiments on ADNI, that our proposed HGIB framework outperforms existing state-of-the-art hypergraph neural networks for Alzheimer's disease prognosis.

The Missing U for Efficient Diffusion Models

no code implementations31 Oct 2023 Sergio Calvo-Ordonez, Chun-Wun Cheng, Jiahao Huang, Lipei Zhang, Guang Yang, Carola-Bibiane Schonlieb, Angelica I Aviles-Rivero

Diffusion Probabilistic Models stand as a critical tool in generative modelling, enabling the generation of complex data distributions.

Denoising Image Generation +1

Traffic Video Object Detection using Motion Prior

no code implementations16 Nov 2023 Lihao Liu, Yanqi Cheng, Dongdong Chen, Jing He, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

In this work, we propose two innovative methods to exploit the motion prior and boost the performance of both fully-supervised and semi-supervised traffic video object detection.

Object object-detection +1

TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations

no code implementations21 Nov 2023 Zhenda Shen, Yanqi Cheng, Raymond H. Chan, Pietro Liò, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

Implicit neural representations (INRs) have garnered significant interest recently for their ability to model complex, high-dimensional data without explicit parameterisation.

Single-Shot Plug-and-Play Methods for Inverse Problems

no code implementations22 Nov 2023 Yanqi Cheng, Lipei Zhang, Zhenda Shen, Shujun Wang, Lequan Yu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

In this work, we introduce Single-Shot PnP methods (SS-PnP), shifting the focus to solving inverse problems with minimal data.

Biophysics Informed Pathological Regularisation for Brain Tumour Segmentation

no code implementations14 Mar 2024 Lipei Zhang, Yanqi Cheng, Lihao Liu, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero

Recent advancements in deep learning have significantly improved brain tumour segmentation techniques; however, the results still lack confidence and robustness as they solely consider image data without biophysical priors or pathological information.

Segmentation

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