| What do we understand about convolutional networks? I Hadji, RP Wildes arXiv preprint arXiv:1803.08834, 2018 | 144 | 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 | 68 | 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 | 56 | 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 | 48 | 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 | 37 | 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 | 27 | 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 | 15 | 2022 |
| Local-to-Global Signature Descriptor for 3D Object Recognition I Hadji, GN DeSouza Asian Conference on Computer Vision, 570-584, 2014 | 15 | 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 | 11 | 2022 |
| What do we understand about convolutional networks? arXiv 2018 I Hadji, RP Wildes arXiv preprint arXiv:1803.08834, 1803 | 10 | 1803 |
| 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 | 9 | 2023 |
| You only need one step: Fast super-resolution with stable diffusion via scale distillation M Noroozi, I Hadji, B Martinez, A Bulat, G Tzimiropoulos European Conference on Computer Vision, 145-161, 2024 | 7 | 2024 |
| 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 | 5 | 2022 |
| 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 | |
| Method and system for learning to temporal align signals with interspersed outliers I Hadji, MA Dvornik, K Derpanis, AD Jepson US Patent 12,164,969, 2024 | 1 | 2024 |
| Depth image dimension reduction using deep belief networks I Hadji, A Jain | 1 | |
| Grounding flow graphs in signals M Dvornik, I Hadji, AD Jepson US Patent 12,223,985, 2025 | | 2025 |
Richard WildesProfessor of Electrical Engineering and Computer Science, York UniversityПотвърден имейл адрес: cse.yorku.ca
