Probabilistic Object Models for Pose Estimation in 2D Images. - Damien Teney; Justus H. Piater (DAGM-Symposium, 2011)

Sampling-Based Multiview Reconstruction without Correspondences for 3D Edges. - Damien Teney; Justus H. Piater (3DIMPVT, 2012)

Generalized Exemplar-Based Full Pose Estimation from 2D Images without Correspondences. - Damien Teney; Justus H. Piater (DICTA, 2012)

Continuous Pose Estimation in 2D Images at Instance and Category Levels. - Damien Teney; Justus H. Piater (CRV, 2013)

Modeling Pose/Appearance Relations for Improved Object Localization and Pose Estimation in 2D images. - Damien Teney; Justus H. Piater (IbPRIA, 2013)

Probabilistic Models of Visual Appearance For Object Identity, Class, and Pose Inference. - Damien Teney (2013)

Segmentation of Dynamic Scenes with Distributions of Spatiotemporally Oriented Energies. - Damien Teney; Matthew Brown 001 (BMVC, 2014)

Multiview feature distributions for object detection and continuous pose estimation. - Damien Teney; Justus H. Piater (Comput. Vis. Image Underst., 2014)

Learning similarity metrics for dynamic scene segmentation. - Damien Teney; Matthew Brown 001; Dimitry Kit; Peter Hall 001 (CVPR, 2015)

Hand parsing for fine-grained recognition of human grasps in monocular images. - Akanksha Saran; Damien Teney; Kris M. Kitani (IROS, 2015)

A hierarchical Bayesian network for face recognition using 2D and 3D facial data. - Iman Abbasnejad; Damien Teney (MLSP, 2015)

Learning to Extract Motion from Videos in Convolutional Neural Networks. - Damien Teney; Martial Hebert (ACCV (5), 2016)

Zero-Shot Visual Question Answering. - Damien Teney; Anton van den Hengel (CoRR, 2016)

Graph-Structured Representations for Visual Question Answering. - Damien Teney; Lingqiao Liu; Anton van den Hengel (CVPR, 2017)

Bottom-Up and Top-Down Attention for Image Captioning and VQA. - Peter Anderson 001; Xiaodong He 001; Chris Buehler; Damien Teney; Mark Johnson 001; Stephen Gould; Lei Zhang 001 (CoRR, 2017)

Visual question answering: A survey of methods and datasets. - Qi Wu 001; Damien Teney; Peng Wang 015; Chunhua Shen; Anthony R. Dick; Anton van den Hengel (Comput. Vis. Image Underst., 2017)

Visual Question Answering: A Tutorial. - Damien Teney; Qi Wu 001; Anton van den Hengel (IEEE Signal Process. Mag., 2017)

Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering. - Peter Anderson 001; Xiaodong He 001; Chris Buehler; Damien Teney; Mark Johnson 001; Stephen Gould; Lei Zhang 001 (CVPR, 2018)

Vision-and-Language Navigation: Interpreting Visually-Grounded Navigation Instructions in Real Environments. - Peter Anderson 001; Qi Wu 001; Damien Teney; Jake Bruce; Mark Johnson 001; Niko Sünderhauf; Ian D. Reid 001; Stephen Gould; Anton van den Hengel (CVPR, 2018)

Tips and Tricks for Visual Question Answering: Learnings From the 2017 Challenge. - Damien Teney; Peter Anderson 001; Xiaodong He 001; Anton van den Hengel (CVPR, 2018)

Visual Question Answering as a Meta Learning Task. - Damien Teney; Anton van den Hengel (ECCV (15), 2018)

Actively Seeking and Learning From Live Data. - Damien Teney; Anton van den Hengel (CVPR, 2019)

On Incorporating Semantic Prior Knowlegde in Deep Learning Through Embedding-Space Constraints. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (CoRR, 2019)

V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices. - Damien Teney; Peng Wang 023; Jiewei Cao; Lingqiao Liu; Chunhua Shen; Anton van den Hengel (AAAI, 2020)

Counterfactual Vision and Language Learning. - Ehsan Abbasnejad; Damien Teney; Amin Parvaneh; Javen Shi; Anton van den Hengel (CVPR, 2020)

Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (ECCV (10), 2020)

Medical Data Inquiry Using a Question Answering Model. - Zhibin Liao; Lingqiao Liu; Qi Wu 001; Damien Teney; Chunhua Shen; Anton van den Hengel; Johan Verjans (ISBI, 2020)

Counterfactual Vision-and-Language Navigation: Unravelling the Unseen. - Amin Parvaneh; Ehsan Abbasnejad; Damien Teney; Qinfeng Shi; Anton van den Hengel (NeurIPS, 2020)

On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law. - Damien Teney; Ehsan Abbasnejad; Kushal Kafle; Robik Shrestha; Christopher Kanan; Anton van den Hengel (NeurIPS, 2020)

Unshuffling Data for Improved Generalization. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (CoRR, 2020)

Visual Question Answering with Prior Class Semantics. - Violetta Shevchenko; Damien Teney; Anthony R. Dick; Anton van den Hengel (CoRR, 2020)

Image Retrieval on Real-life Images with Pre-trained Vision-and-Language Models. - Zheyuan Liu 002; Cristian Rodriguez Opazo; Damien Teney; Stephen Gould (ICCV, 2021)

Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering. - Corentin Dancette; Rémi Cadène; Damien Teney; Matthieu Cord (ICCV, 2021)

Unshuffling Data for Improved Generalization in Visual Question Answering. - Damien Teney; Ehsan Abbasnejad; Anton van den Hengel (ICCV, 2021)

Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge. - Violetta Shevchenko; Damien Teney; Anthony R. Dick; Anton van den Hengel (CoRR, 2021)

Vision-Language Pretraining: Current Trends and the Future. - Aishwarya Agrawal; Damien Teney; Aida Nematzadeh (ACL (tutorial), 2022)

Active Learning by Feature Mixing. - Amin Parvaneh; Ehsan Abbasnejad; Damien Teney; Reza Haffari; Anton van den Hengel; Javen Qinfeng Shi (CVPR, 2022)

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 (CVPR, 2022)

Predicting Is Not Understanding: Recognizing and Addressing Underspecification in Machine Learning. - Damien Teney; Maxime Peyrard; Ehsan Abbasnejad (ECCV (23), 2022)

SelecMix: Debiased Learning by Contradicting-pair Sampling. - Inwoo Hwang; Sangjun Lee; Yunhyeok Kwak; Seong Joon Oh; Damien Teney; Jin-Hwa Kim; Byoung-Tak Zhang (NeurIPS, 2022)

EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering. - Violetta Shevchenko; Ehsan Abbasnejad; Anthony R. Dick; Anton van den Hengel; Damien Teney (CoRR, 2022)

ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets. - Damien Teney; Yong Lin; Seong Joon Oh; Ehsan Abbasnejad (NeurIPS, 2023)

A Symbolic Framework for Systematic Evaluation of Mathematical Reasoning with Transformers. - Jordan Meadows; Marco Valentino; Damien Teney; André Freitas (CoRR, 2023)

Learning Diverse Features in Vision Transformers for Improved Generalization. - Armand Mihai Nicolicioiu; Andrei Liviu Nicolicioiu; Bogdan Alexe; Damien Teney (CoRR, 2023)

Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks. - Luca Scimeca; Alexander Rubinstein 002; Armand Mihai Nicolicioiu; Damien Teney; Yoshua Bengio (CoRR, 2023)

ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learning. - Wang Lu; Hao Yu; Jindong Wang 001; Damien Teney; Haohan Wang; Yiqiang Chen 001; Qiang Yang 001; Xing Xie 001; Xiangyang Ji (CoRR, 2023)

Shortcut Bias Mitigation via Ensemble Diversity Using Diffusion Probabilistic Models. - Luca Scimeca; Alexander Rubinstein 002; Damien Teney; Seong Joon Oh; Armand Mihai Nicolicioiu; Yoshua Bengio (CoRR, 2023)

Zero-shot Retrieval: Augmenting Pre-trained Models with Search Engines. - Hamed Damirchi; Cristian Rodriguez Opazo; Ehsan Abbasnejad; Damien Teney; Javen Qinfeng Shi; Stephen Gould; Anton van den Hengel (CoRR, 2023)

Neural Redshift: Random Networks are not Random Functions. - Damien Teney; Armand Mihai Nicolicioiu; Valentin Hartmann; Ehsan Abbasnejad (CVPR, 2024)

Selective Mixup Helps with Distribution Shifts, But Not (Only) because of Mixup. - Damien Teney; Jindong Wang 001; Ehsan Abbasnejad (ICML, 2024)

A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers. - Jordan Meadows; Marco Valentino; Damien Teney; André Freitas (NAACL-HLT, 2024)

CulturePark: Boosting Cross-cultural Understanding in Large Language Models. - Cheng Li; Damien Teney; Linyi Yang; Qingsong Wen; Xing Xie 001; Jindong Wang 001 (NeurIPS, 2024)

Bi-directional Training for Composed Image Retrieval via Text Prompt Learning. - Zheyuan Liu 002; Weixuan Sun; Yicong Hong; Damien Teney; Stephen Gould (WACV, 2024)

Scalable Ensemble Diversification for OOD Generalization and Detection. - Alexander Rubinstein 002; Luca Scimeca; Damien Teney; Seong Joon Oh (CoRR, 2024)

OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable? - Liangze Jiang; Damien Teney (CoRR, 2024)

Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encoder. - Zheyuan Liu 002; Weixuan Sun; Damien Teney; Stephen Gould (Trans. Mach. Learn. Res., 2024)

Bayesian Low-Rank Learning (Bella): A Practical Approach to Bayesian Neural Networks. - Bao Gia Doan; Afshar Shamsi; Xiao-Yu Guo; Arash Mohammadi 001; Hamid Alinejad-Rokny; Dino Sejdinovic; Damien Teney; Damith C. Ranasinghe; Ehsan Abbasnejad (AAAI, 2025)

Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild. - Damien Teney; Liangze Jiang; Florin Gogianu; Ehsan Abbasnejad (CVPR, 2025)

Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling. - Cristian Rodriguez Opazo; Ehsan Abbasnejad; Damien Teney; Hamed Damirchi; Edison Marrese-Taylor; Anton van den Hengel (ICLR, 2025)

AugGen: Synthetic Augmentation Can Improve Discriminative Models. - Parsa Rahimi; Damien Teney; Sébastien Marcel (CoRR, 2025)

Leaner Transformers: More Heads, Less Depth. - Hemanth Saratchandran; Damien Teney; Simon Lucey (CoRR, 2025)

Transformers Pretrained on Procedural Data Contain Modular Structures for Algorithmic Reasoning. - Zachary Shinnick; Liangze Jiang; Hemanth Saratchandran; Anton van den Hengel; Damien Teney (CoRR, 2025)