\bigstar - Preprint - \bigstar

NorMatch5[P]NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning
Z Deng, R Ke, C-B Schönlieb and AI Aviles-Rivero
Preprint Version — Arxiv-Link
scotchAndSoda5[P]SCOTCH and SODA: A Transformer Video Shadow Detection Framework
L Liu, J Prost, L Zhu, N Papadakis, P Lio, C-B Schönlieb and AI Aviles-Rivero
Preprint Version — Arxiv-Link
robustness5[P]Why Deep Surgical Models Fail?: Revisiting Surgical Action Triplet
Recognition through the Lens of Robustness
Y Cheng, L Liu, S Wang, Y Jin,  C-B Schönlieb and AI Aviles-Rivero
Preprint Version — Arxiv-Link
PCSwinMorph[P]PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation
L Liu,  Z Huang,  P Lio,  C-B Schönlieb and AI Aviles-Rivero
Preprint Version — Arxiv-Link
1graphd[P]Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy
AI Aviles-Rivero, N. Papadakis, R. Li, P Sellars, SM. Alsaleh, R. T Tan and C-B Schönlieb.
Preprint Version– Arxiv-Link
DeepWalkers[P] — Delving into Deep Walkers: A Convergence Analysis of Random-Walk-Based Vertex Embeddings.
D Kloepfer, AI Aviles-Rivero and D Heydecker
Preprint Version — Arxiv-Link
contrastiveRegistration[P] Contrastive Registration for Unsupervised Medical Image Segmentation
L Liu, AI Aviles-Rivero and C-B Schönlieb
Preprint Version — Arxiv-Link
Code Repository
deepRprior[P]Deep Reflection Prior.
Y Yin, Q Fan, D Chen, Y Wang, AI Aviles-Rivero, R Li, C-B Schönlieb, D Lischinsky and B Chen
Preprint Version — Arxiv-Link
deepSSLv55[P]CycleCluster: Modernising Clustering Regularisation for Deep Semi-Supervised Classification
P Sellars, AI Aviles-Rivero and C-B Schönlieb
Preprint Version.
dimf[P] —  Dim the Lights! — Low-Rank Prior Temporal Data for Specular-Free Video Recovery
SM Alsaleh, AI Aviles-Rivero, N Debroux and JK Hahn
Preprint Version.

\bigstar - 2022 - \bigstar

mammography[J] — Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
T Wei, AI Aviles-Rivero, S Wang, Y Huang, FJ Gilbert, CB Schonlieb, CW Chen
Medical Image Analysis (MedIA)
Arxiv-Link || Journal Link
LaplaceNetV2b[J] — LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification
P Sellars, AI Aviles-Rivero and CB Schonlieb
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
Arxiv-Link  || Journal Link || Code Repository
HyperGraphC[C]Multi-Modal Hypergraph Diffusion Network with Dual Prior for Alzheimer Classification
AI Aviles-Rivero, C Runkel, N Papadakis, Z Kourtzi and C-B Schönlieb.
MICCAI 2022 (early accept)
Arxiv-Link  || Conference Link ||  Media
3stageSSLb[J] — A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation
R Ke*, AI Aviles-Rivero*, S Pandey, S Reddy and C-B Schönlieb (*Equal Contribution)
IEEE Transactions on Image Processing
Arxiv-Link || Journal Link ||  Media Coverage
Code Repository
conicChallenge[C] — Simultaneous Semantic and Instance Segmentation for Colon Nuclei Identification and Counting
L Liu,  C Hong, AI Aviles-Rivero and C-B Schönlieb  
MIUA 2022 Preprint Version — Arxiv-Link
🏆 4th Place Cellular Composition CoNIC Grand Challenge 2022 [Leaderboards]
🏆 The NVIDIA merit award
TFPnP1[J] — TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problems.
K. Wei, AI Aviles-Rivero, J Liang, Y. Fu, H Huang and C-B Schönlieb
Journal of Machine Learning Research (JMLR)  Arxiv-Link || Journal Link || Code Repository Extended Version of our ICML 2020 Outstanding Paper Award

\bigstar - 2021 - \bigstar

HERS_SuperpixelsB[C] — HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation
H Peng, AI Aviles-Rivero and CB Schonlieb.
Arxiv-Link || Conference-Paper
Code Repository
B[J] — GraphXCOVID: Explainable Deep Graph Diffusion Pseudo-Labelling for Identifying COVID-19 on Chest X-rays
AI Aviles-Rivero, P Sellars, C-B Schönlieb and N Papadakis
Pattern Recognition
Arxiv-Link || Journal Link  ||  Media Coverage
Radiology2[J] — Machine Learning for Workflow Applications in Screening Mammography: Systematic Review and Meta-Analysis
S Hickman, R Woitek, EPV Le, YR Im, C Luxhøj, AI Aviles-Rivero, GC Baxter, JW MacKay, FJ Gilbert 
Radiology  Journal Link  
FastMRI5[J] —Learning Optical Flow for Fast MRI Reconstruction.
T Schmoderer, AI Aviles-Rivero, V Corona, N Debroux and CB Schonlieb
Inverse Problems
Arxiv-Link || Journal Link  
Code Repository
updatedCS+m2[J] — Compressed Sensing Plus Motion (CS+M): A New Perspective for Improving Undersampled MR Image Reconstruction.
A.I Aviles-Rivero, N Debroux, G. Williams, M.J. Graves and C-B Schönlieb.  Medical Image Analysis (MedIA)
Arxiv-Link || Journal Link
covidreview2[J] — Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
M Roberts, D Driggs, M Thorpe, J Gilbey, M Yeung, S Ursprung, AI Aviles-Rivero, C Etmann, et al. & C-B Schönlieb. Nature Machine Intelligence
Arxiv-Link || Journal Link

\bigstar - 2020 - \bigstar

TEASER5[J] — Variational Multi-Task MRI Reconstruction: Joint Reconstruction, Registration and Super-Resolution
V. Corona, A.I Aviles-Rivero, N Debroux, C. Le Guyader and C-B Schönlieb. To appear in Medical Image Analysis (MedIA)
Preprint Version.  Arxiv-Link || Journal Link
CTrec[J] — Rethinking Medical Image Reconstruction via Shape Prior, Going Deeper and Faster: Deep Joint Indirect Registration and Reconstruction.
J Liu, AI Aviles-Rivero, H Ji and C-B Schönlieb.  Medical Image Analysis (MedIA)
Preprint Version — Arxiv-Link || Journal Link
SRsuperpixels[J] — Dynamic Spectral Residual Superpixels.
J. Zhang*, A.I Aviles-Rivero*, D Heydecker*, X Zhuang, R. Chan and C-B Schönlieb.  Pattern Recognition.
(*Equal Contribution).
Preprint Version. Arxiv-Link || Journal Link
graphNetZoo[C]The GraphNet Zoo: An All-in-One Graph Based Deep Semi-Supervised Framework for Medical Image Classification. M de Vriendt*, P Sellars* and A.I Aviles-Rivero* (*Equal Contribution)
To appear- GRaphs in biomedicAl Image anaLysis (GRAIL2020) Satellite Event MICCAI2020. Arxiv-Link
AdaptiveFilterBank[J] Controllable Image Processing via Adaptive FilterBank Pyramid. D Chen, Q Fan, J Liao, AI Aviles-Rivero, L Yuan, N Yu, G Hua
IEEE Transactions on Image Processing (TIP)
Jornal Link
PnP[C]Tuning-free Plug-and-Play Proximal Algorithm for Inverse Imaging Problems.
K. Wei, AI Aviles-Rivero, J Liang, Y. Fu, C-B Schönlieb and H Huang
International Conference on Machine Learning (ICML) Arxiv-Link
Outstanding Paper Awardtrophy
Code Repository
teaser2.png[J] — Superpixel Contracted Graph-Based Learning for Hyperspectral Image Classification.
P. Sellars, A.I Aviles-Rivero and C-B Schönlieb.
IEEE Transactions on Geoscience and Remote Sensing (TGRS).
Arxiv-Link ||Journal Link
Code Repository


\bigstar - 2019 - \bigstar

ICCV19b[C] —RainFlow: Optical Flow under Rain Streaks and Rain Veiling Effect.
R. Li, RT Tan, LF Cheong, A.I Aviles-RiveroQ. Fan and C-B Schönlieb.
IEEE/CVF International Conference on Computer Vision (ICCV)
Conference Link 
Code Repository
teaserMICCAI19[C] — GraphXNET – Chest X-Ray Classification Under Extreme Minimal Supervision.
A.I Aviles-Rivero*,  N. Papadakis*, R. Li, P. Sellars, Q. Fan, R. T Tan and C-B Schönlieb.
MICCAI ’19 (early accept)
Arxiv-Link || Conference Link
MirrorPaper.png[J] — Mirror, Mirror, on the Wall, Who’s Got the Clearest Image of Them All? − A Tailored Approach to Single Image Reflection Removal.
D. Heydecker*, G. Maierhofer*,A.I Aviles-Rivero*, Q. Fan, D. Chen, C-B Schönlieb and S. Süsstrunk. (*Equal Contribution).
IEEE Transactions on Image Processing (TIP) — Arxiv-Link || Jornal Link
sslpaper[C] Semi-supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification.
P. Sellars, A.I Aviles-Rivero, N. Papadakis, D. Coomes, A. Faul and C-B Schönlieb. (Oral)
To appear IEEE IGARSS 2019.
Preprint || ConferenceVersion
Specular_Scheme_[J] — ReTouchImg: Fusioning From-Local-to-Global Context Detection and Graph Data Structures for Fully-Automatic Specular Reflection Removal for Endoscopic Images.
S.M. Alsaleh, A.I Aviles-Rivero and JK Hanh.
Computerized Medical Imaging and Graphics.  Journal Link
ssvmVisualisation.png[C] — Multi-tasking to Correct: Motion-CompensatedMRI via Joint Reconstruction and Registration.
V. Corona, A.I Aviles-Rivero, N. Debroux, M. Graves, C. Le Guyader, C-B Schönlieb and G. Williams. Scale Space and Variational Methods in Computer Vision (SSVM19).  
Preprint || ConferenceVersion
Fig1_teaserC[C] — Motion Correction Resolved for MRI via Multi-Tasking: A Simultaneous Reconstruction and Registration Approach.
V. Corona, N. Debroux, A.I Aviles-Rivero,  M. Graves, G. Williams, C. Le Guyader and C-B Schönlieb
ISMRM 2019.

\bigstar - 2018 - \bigstar

introFigC_5a[C]Peekaboo – Where are the Objects? Structure Adjusting Superpixels.
G. Maierhofer*, D. Heydecker*, A.I Aviles-Rivero*, S.M Alsaleh and C-B Schönlieb. (*Equal Contribution)  ICIP2018.
Preprint || ConferenceVersion
CS+M[C] — CS+M: A Simultaneous Reconstruction and Motion Estimation Approach for Improving Undersampled MRI Reconstruction.
A.I Aviles-Rivero, G. Williams, M. Graves and C.B Schönlieb.
ISMRM 2018.
robotic_scheme[J] — Sensory Substitution for Force Feedback Recovery: A Perception Experimental Study.
A.I Aviles-Rivero, S.M Alsaleh, J. Philbeck, S.P Raventos, N. Younes, J.K Hanh and A. Casals
ACM Transactions on Applied Perception (TAP), 2018. Journal Link
robotic_scheme5.png[J] — Sliding to predict: Vision-based beating heart motion estimation by modeling temporal interactions.
A.I Aviles-Rivero, S.M Alsaleh and A. Casals.
International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2018.
Journal Link

\bigstar - 2017 - \bigstar

ultra_scheme[J] — Robust Cardiac Motion Estimation using Ultrafast Ultrasound Data: A Low-Rank Topology-Preserving Approach.
A.I Aviles-Rivero, T. Widlak, A. Casals, M.M. Nillesen and H. Ammari.
Physics in Medicine and Biology, 2017.
|| Journal Link
scheme1b-e1534090032815[J] Towards Retrieving Force Feedback in Robotic-Assisted Surgery: A Supervised Neuro-Recurrent-Vision Approach.
A.I Aviles-Rivero, S.M Alsaleh, J.K. Hahn and A. Casals.
IEEE Transactions on Haptics, 2017.   —  Journal Link
IROS2017[C] — Sight to Touch: 3D Diffeomorphic Deformation Recovery with Mixture Components for Perceiving Forces in Robotic-Assisted Surgery.
A.I Aviles-Rivero, S.M. Alsaleh and A. Casals.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017. Vancouver, Canada. Paper
siggrpah17A[C] — Escaping specularity: recovering specular-free video sequences from rank-constrained data.
S.M. Alsaleh, A.I Aviles-Rivero, A. Casals and J.K. Hahn.
SIGGRAPH Posters 2017. L.A., California, USA.  Paper Link

\bigstar - 2016 - \bigstar

EMBC16[C] — Towards Estimating Cardiac Motion Using Low-Rank Representation and Topology Preservation for Ultrafast Ultrasound Data.
A.I Aviles-Rivero, T. Widlak, A. Casals and H. Ammari. IEEE Engineering in Medicine and Biology Society (EMBC) 2016. –Paper Link
fuzz16b[C] — A Deep-Neuro-Fuzzy Approach for Estimating the Interaction Forces in Robotic Surgery. A.I Aviles-Rivero, S.M. Alsaleh, E. Montseny, P. Sobrevilla, and A. Casals. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) 2016. (Oral) –Paper Link
SPIEImaging16[C] — Exploring the Effects of Dimensionality Reduction in Deep Networks for Force Estimation in Robotic-Assisted Surgery. A.I Aviles-Rivero, S. Alsaleh, P. Sobrevilla, and A. Casals. SPIE Medical Imaging, 2016. –Paper Link

\bigstar - 2015 - \bigstar

embc15.png[C] — Force-Feedback Sensory Substitution Using Supervised Recurrent Learningfor Robotic-Assisted Surgery. A.I Aviles-Rivero, S.M. Alsaleh, P. Sobrevilla, and A. Casals. IEEE Engineering in Medicine and Biology Society (EMBC) 2015. (Oral). –Paper Link
embc15alsaleh[C] — Automatic and Robust Single-Camera Specular Highlight Removal in Cardiac Images. S.M. Alsaleh, A.I Aviles-Rivero, P. Sobrevilla, A. Casals and JK Hahn. IEEE Engineering in Medicine and Biology Society (EMBC) 2015. –Paper Link
NER15[C] — Sensorless force estimation using a neuro-vision-based approach for robotic-assisted surgery. A.I Aviles-Rivero, S.M. Alsaleh, P. Sobrevilla, A. Casals and JK Hahn. International IEEE/EMBS Conference on Neural Engineering (NER) 2015. –Paper Link