Damien Teney
WORKING WITH US
The machine learning group at Idiap is always looking for talented and motivated people.
Open positions are advertised through the Jobs page of the institute website.
For code and resources, follow the links in the relevant publications. For the older projects, see the code archive .
PUBLICATIONS
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization
Damien Teney, Ehsan Abbasnejad, Simon Lucey, Anton van den Hengel.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
[ arXiv ]
Active Learning by Feature Mixing
Amin Parvaneh, Ehsan Abbasnejad, Damien Teney, Reza Haffari, Anton van den Hengel, Javen Qinfeng Shi
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022.
[ arXiv ]
Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models
Zheyuan Liu, Cristian Rodriguez-Opazo, Damien Teney, Stephen Gould
IEEE/CVF International Conference on Computer Vision, 2021.
[ arXiv ] [ project page ]
Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering
Corentin Dancette, Remi Cadene, Damien Teney, Matthieu Cord.
IEEE/CVF International Conference on Computer Vision, 2021.
[ arXiv ]
Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge
Violetta Shevchenko, Damien Teney, Anthony Dick, Anton van den Hengel.
Workshop on Beyond Vision and LANguage: inTEgrating Real-world kNowledge (LANTERN), EACL, 2021.
[ arXiv ]
On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law
Damien Teney, Kushal Kafle, Robik Shrestha, Ehsan Abbasnejad, Christopher Kanan, Anton van den Hengel.
NeurIPS, 2020.
[ arXiv ]
Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision
Damien Teney, Ehsan Abbasnejad, Anton van den Hengel.
European Conference on Computer VIsion (ECCV), 2020.
[ arXiv ]
Unshuffling Data for Improved Generalization
Damien Teney, Ehsan Abbasnejad, Anton van den Hengel.
arXiv Preprint [cs.CV], 2020.
[ arXiv ]
Visual Question Answering with Prior Class Semantics
Violetta Shevchenko, Damien Teney, Anthony Dick, Anton van den Hengel.
arXiv Preprint [cs.CV], 2020.
[ arXiv ]
Counterfactual Vision and Language Learning
Ehsan Abbasnejad, Damien Teney, Amin Parvaneh, Javen Shi, Anton van den Hengel.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.
Medical Data Inquiry Using a Question Answering Model
Zhibin Liao, Lingqiao Liu, Qi Wu, Damien Teney, Chunhua Shen, Johan Verjans, Anton van Hengel.
IEEE International Symposium on Biomedical Imaging (ISBI), 2020.
V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices
Damien Teney, Peng Wang, Jiewei Cao, Lingqiao Liu, Chunhua Shen, Anton van den Hengel.
AAAI, 2020.
[ arXiv ] [ dataset available on request ]
On Incorporating Semantic Prior Knowlegde in Deep Learning Through Embedding-Space Constraints
Damien Teney, Ehsan Abbasnejad, Anton van den Hengel.
arXiv Preprint [cs.CV,cs.LG], 2019.
[ arXiv ]
Actively Seeking and Learning from Live Data
Damien Teney, Anton van den Hengel.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
[ arXiv ]
Visual Question Answering as a Meta Learning Task
Damien Teney, Anton van den Hengel.
European Conference on Computer Vision (ECCV), 2018.
[ arXiv ]
Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments
Peter Anderson, Qi Wu, Damien Teney, Jake Bruce, Mark Johnson, Niko Sünderhauf, Ian Reid, Stephen Gould, Anton van den Hengel.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[ arXiv ]
Tips and Tricks for Visual Question Answering: Learnings from the 2017 Challenge
Damien Teney, Peter Anderson, Xiaodong He, Anton van den Hengel.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[ arXiv ] Winner of the 2017 Visual Question Answering challenge at CVPR.
Bottom-Up and Top-Down Attention for Image Captioning and VQA
Peter Anderson, Xiaodong He, Chris Buehler, Damien Teney, Mark Johnson, Stephen Gould, Lei Zhang.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
[ arXiv ]
Visual Question Answering; A Tutorial
Damien Teney, Qi Wu, Anton van den Hengel.
IEEE Signal Processing Magazine 34 (6), 63-75, 2017.
[ IEEE Xplore ]
Graph-Structured Representations for Visual Question Answering
Damien Teney, Lingqiao Liu, Anton van den Hengel.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
[ arXiv ]
Visual Question Answering: A Survey of Methods and Datasets
Qi Wu, Damien Teney, Peng Wang, Chunhua Shen, Anthony Dick, Anton van den Hengel.
Computer Vision and Image Understanding (CVIU), 2017.
[ arXiv ]
Zero-Shot Visual Question Answering
Damien Teney, Anton van den Hengel.
arXiv Preprint [cs.CV], 2016.
[ arXiv ]
Learning to Extract Motion from Videos in Convolutional Neural Networks
Damien Teney, Martial Hebert.
Asian Conference on Computer Vision (ACCV), 2016.
[ arXiv ]
Learning Filter-Based Motion Features for Dynamic Scene Analysis
Damien Teney, Martial Hebert.
Scene Understanding Workshop at CVPR, 2015.
A Hierarchical Bayesian Network for Face Recognition Using 2D and 3D Facial Data
Iman Abbasnejad, Damien Teney.
IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 2015.
Hand Parsing for Fine-Grained Recognition of Human Grasps in Monocular Images
Akanksha Saran, Damien Teney, Kris M. Kitani.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2015. Also appeard at the Workshop on Observing and Understanding Hands in Action at CVPR, 2015.
Learning Similarity Metrics for Dynamic Scene Segmentation
Damien Teney, Matthew Brown, Dimitry Kit, Peter Hall.
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015.
Segmentation of Dynamic Scenes with Distributions of Spatiotemporally Oriented Energies
Damien Teney, Matthew Brown.
British Machine Vision Conference (BMVC), 2014.
Segmentation of Low-Level Motion Features to Infer Occlusion Boundaries and Local Depth Ordering
Damien Teney, Matthew Brown.
Scene Understanding Workshop at CVPR, 2014.
Multi-view Feature Distributions for Object Detection and Continuous Pose Estimation
Damien Teney, Justus Piater.
Computer Vision and Image Understanding (CVIU), 125, pp. 265–282, 2014.
Probabilistic Models of Visual Appearance for Object Identity, Class, and Pose Inference
Damien Teney.
PhD Thesis, University of Liege, 2013.
Markerless Self-Recognition and Segmentation of Robotic Manipulator in Still Images
Damien Teney, Dadhichi Shukla, Justus Piater.
Mobile Manipulation Workshop on Interactive Perception at the IEEE International Conference on Robotics and Automation (ICRA), 2013.
Modeling Pose/Appearance Relations for Improved Object Localization and Pose Estimation in 2D Images
Damien Teney, Justus Piater.
Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA), pp. 59-68, 2013. Springer LNCS 7887/2013.
Continuous Pose Estimation in 2D Images at Instance and Category Levels
Damien Teney, Justus Piater.
Computer and Robot Vision (CRV), 2013.
Best Vision paper award.
Generalized Exemplar-Based Full Pose Estimation from 2D Images without Correspondences
Damien Teney, Justus Piater.
Digital Image Computing: Techniques and Applications (DICTA), 2012.
Sampling-based Multiview Reconstruction without Correspondences for 3D Edges
Damien Teney, Justus Piater.
3DimPVT, 2012.
Probabilistic Object Models for Pose Estimation in 2D Images
Damien Teney, Justus Piater.
DAGM, pp. 336–345, 2011. Springer LNCS 6835/2011.