José Oramas M.

According to our database, José Oramas M. authored at least 58 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

SNIPPET: A Framework for Subjective Evaluation of Visual Explanations Applied to DeepFake Detection.

Yuqing Yang, Boris Joukovsky, José Oramas Mogrovejo, Tinne Tuytelaars, Nikos Deligiannis

ACM Trans. Multim. Comput. Commun. Appl., August, 2024

On the coherency of quantitative evaluation of visual explanations.

Benjamin Vandersmissen, José Oramas

Comput. Vis. Image Underst., 2024

Bilinear MLPs enable weight-based mechanistic interpretability.

Michael T. Pearce, Thomas Dooms, Alice Rigg, José Oramas M., Lee Sharkey

CoRR, 2024

Enhancing Hyperspectral Image Prediction with Contrastive Learning in Low-Label Regime.

Salma Haidar, José Oramas

CoRR, 2024

Deep Model Interpretation with Limited Data : A Coreset-based Approach.

Hamed Behzadi-Khormouji, José Oramas

CoRR, 2024

Smooth InfoMax - Towards easier Post-Hoc interpretability.

Fabian Denoodt, Bart de Boer, José Oramas

CoRR, 2024

Recognizing Actions in High-Resolution Low-Framerate Videos: A Feasibility Study in the Construction Sector.

Benjamin Vandersmissen, Arian Sabaghi, Philippe Reiter, José Oramas

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

Deep Learning Model Compression for Resource Efficient Activity Recognition on Edge Devices: A Case Study.

Dieter Balemans, Benjamin Vandersmissen, Jan Steckel, Siegfried Mercelis, Philippe Reiter, José Oramas

Proceedings of the 19th International Joint Conference on Computer Vision, 2024

2023

Training Methods of Multi-Label Prediction Classifiers for Hyperspectral Remote Sensing Images.

Salma Haidar, José Oramas

Remote. Sens., December, 2023

The Trifecta: Three simple techniques for training deeper Forward-Forward networks.

Thomas Dooms, Ing Jyh Tsang, José Oramas

CoRR, 2023

FICNN: A Framework for the Interpretation of Deep Convolutional Neural Networks.

Hamed Behzadi-Khormouji, José Oramas

CoRR, 2023

Towards the Characterization of Representations Learned via Capsule-based Network Architectures.

Saja AL-Tawalbeh, José Oramas

CoRR, 2023

Considering Layerwise Importance in the Lottery Ticket Hypothesis.

Benjamin Vandersmissen, José Oramas

CoRR, 2023

On The Coherence of Quantitative Evaluation of Visual Expalantion.

Benjamin Vandersmissen, José Oramas

CoRR, 2023

A Contrastive Learning Method for Multi-Label Predictors on Hyperspectral Images.

Salma Haidar, José Oramas

Proceedings of the 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2023

A Protocol for Evaluating Model Interpretation Methods from Visual Explanations.

Hamed Behzadi Khormuji, José Oramas

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Human Motion Prediction on the IKEA-ASM Dataset.

Mattias Billast, Kevin Mets, Tom De Schepper, José Oramas, Steven Latré

Proceedings of the 18th International Joint Conference on Computer Vision, 2023

Automated Virtual Reduction of Displaced Distal Radius Fractures.

Jana Osstyn, Femke Danckaers, Annemieke Van Haver, José Oramas, Matthias Vanhees, Jan Sijbers

Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Interpreting Convolutional Neural Networks by Explaining Their Predictions.

Toon Meynen, Hamed Behzadi-Khormouji, José Oramas

Proceedings of the IEEE International Conference on Image Processing, 2023

2022

Deep Set Conditioned Latent Representations for Action Recognition.

Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré

Proceedings of the 17th International Joint Conference on Computer Vision, 2022

Object Detection To Enable Autonomous Vessels On European Inland Waterways.

Mattias Billast, Robin Janssens, Astrid Vanneste, Simon Vanneste, Olivier Vasseur, Ali Anwar, Kevin Mets, Tom De Schepper, José Oramas, Steven Latré, Peter Hellinckx

Proceedings of the IECON 2022, 2022

AIMLAI: Advances in Interpretable Machine Learning and Artificial Intelligence.

Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

MinMaxCAM: Improving object coverage for CAM-basedWeakly Supervised Object Localization.

Kaili Wang, José Oramas M., Tinne Tuytelaars

CoRR, 2021

Towards Human-Understandable Visual Explanations: Imperceptible High-frequency Cues Can Better Be Removed.

Kaili Wang, José Oramas M., Tinne Tuytelaars

CoRR, 2021

Task Independent Capsule-Based Agents for Deep Q-Learning.

Akash Singh, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré

Proceedings of the Artificial Intelligence and Machine Learning, 2021

Object Detection with Semi-supervised Adversarial Domain Adaptation for Real-Time Edge Devices.

Mattias Billast, Tom De Schepper, Kevin Mets, Peter Hellinckx, José Oramas, Steven Latré

Proceedings of the Artificial Intelligence and Machine Learning, 2021

MinMaxCAM: Improving object coverage for CAM-based Weakly Supervised Object Localization.

Kaili Wang, José Oramas, Tinne Tuytelaars

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

2020

Can the state of relevant neurons in a deep neural networks serve as indicators for detecting adversarial attacks?

Roger Granda, Tinne Tuytelaars, José Oramas M.

CoRR, 2020

Multiple Exemplars-based Hallucinationfor Face Super-resolution and Editing.

Kaili Wang, José Oramas M., Tinne Tuytelaars

CoRR, 2020

Unpaired Image-To-Image Shape Translation Across Fashion Data.

Kaili Wang, Liqian Ma, José Oramas M., Luc Van Gool, Tinne Tuytelaars

Proceedings of the IEEE International Conference on Image Processing, 2020

AIMLAI'20: Third Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence.

Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

In Defense of LSTMs for Addressing Multiple Instance Learning Problems.

Kaili Wang, José Oramas M., Tinne Tuytelaars

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

Multiple Exemplars-Based Hallucination for Face Super-Resolution and Editing.

Kaili Wang, José Oramas M., Tinne Tuytelaars

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019

An Iterative Approach for Multiple Instance Learning Problems.

Kaili Wang, José Oramas M., Tinne Tuytelaars

CoRR, 2019

Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks.

José Oramas M., Kaili Wang, Tinne Tuytelaars

Proceedings of the 7th International Conference on Learning Representations, 2019

Towards Object Shape Translation Through Unsupervised Generative Deep Models.

Lies Bollens, Tinne Tuytelaars, José Oramas M.

Proceedings of the 2019 IEEE International Conference on Image Processing, 2019

Interpreting and Explaining Deep Models Visually.

José Oramas M., Kaili Wang, Tinne Tuytelaars

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

A Systematic Analysis of a Context Aware Deep Learning Architecture for Object Detection.

Kevin Bardool, Tinne Tuytelaars, José Oramas M.

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

A Context Aware Deep Learning Architecture for Object Detection.

Kevin Bardool, Tinne Tuytelaars, José Oramas M.

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

2018

Integrated unpaired appearance-preserving shape translation across domains.

Kaili Wang, Liqian Ma, José Oramas M., Luc Van Gool, Tinne Tuytelaars

CoRR, 2018

An Analysis of Human-Centered Geolocation.

Kaili Wang, Yu-Hui Huang, José Oramas M., Luc Van Gool, Tinne Tuytelaars

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

From Pixels to Actions: Learning to Drive a Car with Deep Neural Networks.

Jonas Heylen, Seppe Iven, Bert De Brabandere, José Oramas M., Luc Van Gool, Tinne Tuytelaars

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

2017

Rank Pooling for Action Recognition.

Basura Fernando, Efstratios Gavves, José Oramas Mogrovejo, Amir Ghodrati, Tinne Tuytelaars

IEEE Trans. Pattern Anal. Mach. Intell., 2017

Context-based object viewpoint estimation: A 2D relational approach.

José Oramas M., Luc De Raedt, Tinne Tuytelaars

Comput. Vis. Image Underst., 2017

2016

Recovering hard-to-find object instances by sampling context-based object proposals.

José Oramas M., Tinne Tuytelaars

Comput. Vis. Image Underst., 2016

Reasoning about Body-Parts Relations for Sign Language Recognition.

Marc Martínez-Camarena, José Oramas M., Mario Montagud Climent, Tinne Tuytelaars

CoRR, 2016

Modeling Visual Compatibility through Hierarchical Mid-level Elements.

José Oramas M., Tinne Tuytelaars

CoRR, 2016

2015

Context-based Reasoning for Object Detection and Object Pose Estimation ; Gebruik van context voor voorwerpherkenning en pose estimatie.

José Oramas Mogrovejo

PhD thesis, 2015

Towards sign language recognition based on body parts relations.

Marc Martínez-Camarena, José Oramas M., Tinne Tuytelaars

Proceedings of the 2015 IEEE International Conference on Image Processing, 2015

Modeling video evolution for action recognition.

Basura Fernando, Efstratios Gavves, José Oramas M., Amir Ghodrati, Tinne Tuytelaars

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

2014

There are plenty of places like home: Using relational representations in hierarchies for distance-based image understanding.

Laura Antanas, Martijn van Otterlo, José Oramas Mogrovejo, Tinne Tuytelaars, Luc De Raedt

Neurocomputing, 2014

Towards cautious collective inference for object verification.

José Oramas M., Luc De Raedt, Tinne Tuytelaars

Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2014

Scene-driven Cues for Viewpoint Classification for Elongated Object Classes.

José Oramas M., Tinne Tuytelaars

Proceedings of the British Machine Vision Conference, 2014

2013

Rule-based Hand Posture Recognition using Qualitative Finger Configurations Acquired with the Kinect.

Lieven Billiet, José Oramas M., McElory Hoffmann, Wannes Meert, Laura Antanas

Proceedings of the ICPRAM 2013, 2013

Allocentric Pose Estimation.

José Oramas M., Luc De Raedt, Tinne Tuytelaars

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

A Relational Distance-based Framework for Hierarchical Image Understanding.

Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt

Proceedings of the ICPRAM 2012, 2012

2011

Potential benets in the learning process of Ecuadorian Sign Language using a Sign Recognition System.

José Oramas Mogrovejo, Alejandro Manuel Moreno Celleri, Katherine Chiluiza García

e Minds Int. J. Hum. Comput. Interact., 2011

2010

Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses.

Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt

Proceedings of the Inductive Logic Programming - 20th International Conference, 2010