| What do we understand about convolutional networks? I Hadji, RP Wildes arXiv preprint arXiv:1803.08834, 2018 | 139 | 2018 |
| Representation learning via global temporal alignment and cycle-consistency I Hadji, KG Derpanis, AD Jepson Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 59 | 2021 |
| Drop-dtw: Aligning common signal between sequences while dropping outliers M Dvornik, I Hadji, KG Derpanis, A Garg, A Jepson Advances in Neural Information Processing Systems 34, 13782-13793, 2021 | 44 | 2021 |
| P3iv: Probabilistic procedure planning from instructional videos with weak supervision H Zhao, I Hadji, N Dvornik, KG Derpanis, RP Wildes, AD Jepson Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 39 | 2022 |
| A Spatiotemporal Oriented Energy Network for Dynamic Texture Recognition I Hadji, RP Wildes IEEE International Conference on Computer Vision (ICCV), 2017 | 39 | 2017 |
| A new large scale dynamic texture dataset with application to convnet understanding I Hadji, RP Wildes Proceedings of the European Conference on Computer Vision (ECCV), 320-335, 2018 | 33 | 2018 |
| Stepformer: Self-supervised step discovery and localization in instructional videos N Dvornik, I Hadji, R Zhang, KG Derpanis, RP Wildes, AD Jepson Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 21 | 2023 |
| Flow graph to video grounding for weakly-supervised multi-step localization N Dvornik, I Hadji, H Pham, D Bhatt, B Martinez, A Fazly, AD Jepson European Conference on Computer Vision, 319-335, 2022 | 14 | 2022 |
| Local-to-Global Signature Descriptor for 3D Object Recognition I Hadji, GN DeSouza Asian Conference on Computer Vision, 570-584, 2014 | 14 | 2014 |
| Prediction of diffusional conductance in extracted pore network models using convolutional neural networks N Misaghian, M Agnaou, MA Sadeghi, H Fathiannasab, I Hadji, E Roberts, ... Computers & Geosciences 162, 105086, 2022 | 9 | 2022 |
| What do we understand about convolutional networks? arXiv 2018 I Hadji, RP Wildes arXiv preprint arXiv:1803.08834, 1803 | 8 | 1803 |
| Graph2vid: Flow graph to video grounding for weakly-supervised multi-step localization N Dvornik, I Hadji, H Pham, D Bhatt, B Martinez, A Fazly, AD Jepson arXiv preprint arXiv:2210.04996, 2022 | 6 | 2022 |
| Gepsan: Generative procedure step anticipation in cooking videos MA Abdelsalam, SB Rangrej, I Hadji, N Dvornik, KG Derpanis, A Fazly Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 5 | 2023 |
| What do we understand about convolutional networks. arXiv I Hadji, RP Wildes arXiv preprint arXiv:1803.08834, 2018 | 5 | 2018 |
| Why convolutional networks learn oriented bandpass filters: Theory and empirical support I Hadji, RP Wildes arXiv preprint arXiv:2011.14665, 2020 | 4 | 2020 |
| Clustering algorithms used in 3D scene segmentation I Hadji, D Nabelek | 2 | |
| You Only Need One Step: Fast Super-Resolution with Stable Diffusion via Scale Distillation M Noroozi, I Hadji, B Martinez, A Bulat, G Tzimiropoulos arXiv preprint arXiv:2401.17258, 2024 | 1 | 2024 |
| Depth Image Dimension Reduction Using Deep Belief Networks I Hadji, A Jain | 1 | |
| Probabilistic procedure planning for instructional videos H Zhao, MA Dvornik, I Hadji, R Wildes, K Derpanis, AD Jepson US Patent 12,050,640, 2024 | | 2024 |
| Step discovery and localization in instructional videos using a self-supervised transformer M Dvornik, I Hadji, R Zhang, K Derpanis, R Wildes, G Animesh, ... US Patent App. 18/227,560, 2024 | | 2024 |
Richard WildesProfessor of Electrical Engineering and Computer Science, York UniversityVerified email at cse.yorku.ca
