| Benchmark analysis of representative deep neural network architectures S Bianco, R Cadene, L Celona, P Napoletano IEEE access 6, 64270-64277, 2018 | 1004 | 2018 |
| Mutan: Multimodal tucker fusion for visual question answering H Ben-Younes, R Cadene, M Cord, N Thome Proceedings of the IEEE international conference on computer vision, 2612-2620, 2017 | 764 | 2017 |
| Rubi: Reducing unimodal biases for visual question answering R Cadene, C Dancette, M Cord, D Parikh Advances in neural information processing systems 32, 2019 | 432 | 2019 |
| Murel: Multimodal relational reasoning for visual question answering R Cadene, H Ben-Younes, M Cord, N Thome Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 359 | 2019 |
| Block: Bilinear superdiagonal fusion for visual question answering and visual relationship detection H Ben-Younes, R Cadene, N Thome, M Cord Proceedings of the AAAI conference on artificial intelligence 33 (01), 8102-8109, 2019 | 261 | 2019 |
| Cross-modal retrieval in the cooking context: Learning semantic text-image embeddings M Carvalho, R Cadène, D Picard, L Soulier, N Thome, M Cord The 41st International ACM SIGIR Conference on Research & Development in …, 2018 | 242 | 2018 |
| What i cannot predict, i do not understand: A human-centered evaluation framework for explainability methods J Colin, T Fel, R Cadène, T Serre Advances in neural information processing systems 35, 2832-2845, 2022 | 96 | 2022 |
| Beyond question-based biases: Assessing multimodal shortcut learning in visual question answering C Dancette, R Cadene, D Teney, M Cord Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 84 | 2021 |
| Craft: Concept recursive activation factorization for explainability T Fel, A Picard, L Bethune, T Boissin, D Vigouroux, J Colin, R Cadène, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 77 | 2023 |
| Look at the variance! efficient black-box explanations with sobol-based sensitivity analysis T Fel, R Cadène, M Chalvidal, M Cord, D Vigouroux, T Serre Advances in neural information processing systems 34, 26005-26014, 2021 | 69 | 2021 |
| How good is your explanation? algorithmic stability measures to assess the quality of explanations for deep neural networks T Fel, D Vigouroux, R Cadène, T Serre Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 44 | 2022 |
| Don't lie to me! robust and efficient explainability with verified perturbation analysis T Fel, M Ducoffe, D Vigouroux, R Cadène, M Capelle, C Nicodème, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 37 | 2023 |
| Xplique: A deep learning explainability toolbox T Fel, L Hervier, D Vigouroux, A Poche, J Plakoo, R Cadene, M Chalvidal, ... arXiv preprint arXiv:2206.04394, 2022 | 34 | 2022 |
| M2CAI workflow challenge: Convolutional neural networks with time smoothing and hidden Markov model for video frames classification R Cadene, T Robert, N Thome, M Cord arXiv preprint arXiv:1610.05541, 2016 | 28 | 2016 |
| A holistic approach to unifying automatic concept extraction and concept importance estimation T Fel, V Boutin, L Béthune, R Cadène, M Moayeri, L Andéol, M Chalvidal, ... Advances in Neural Information Processing Systems 36, 2024 | 25 | 2024 |
| Same-different conceptualization: a machine vision perspective M Ricci, R Cadène, T Serre Current Opinion in Behavioral Sciences 37, 47-55, 2021 | 23 | 2021 |
| Understanding the computational demands underlying visual reasoning M Vaishnav, R Cadene, A Alamia, D Linsley, R VanRullen, T Serre Neural Computation 34 (5), 1075-1099, 2022 | 20 | 2022 |
| Pretrained models for pytorch R Cadene URL https://github. com/Cadene/pretrained-models. pytorch 5, 2018 | 18 | 2018 |
| Master's Thesis: Deep Learning for Visual Recognition R Cadène, N Thome, M Cord arXiv preprint arXiv:1610.05567, 2016 | 14 | 2016 |
| Unlocking feature visualization for deeper networks with magnitude constrained optimization T Fel, T Boissin, V Boutin, A Picard, P Novello, J Colin, D Linsley, ... arXiv preprint arXiv:2306.06805, 2023 | 8 | 2023 |