| Open category detection with PAC guarantees S Liu, R Garrepalli, T Dietterich, A Fern, D Hendrycks International Conference on Machine Learning, 3169-3178, 2018 | 104 | 2018 |
| Panoptic, instance and semantic relations: A relational context encoder to enhance panoptic segmentation S Borse, H Park, H Cai, D Das, R Garrepalli, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 15* | 2022 |
| Distractflow: Improving optical flow estimation via realistic distractions and pseudo-labeling J Jeong, H Cai, R Garrepalli, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 9 | 2023 |
| Pac guarantees and effective algorithms for detecting novel categories S Liu, R Garrepalli, D Hendrycks, A Fern, D Mondal, TG Dietterich Journal of Machine Learning Research 23 (44), 1-47, 2022 | 8 | 2022 |
| Dejavu: Conditional regenerative learning to enhance dense prediction S Borse, D Das, H Park, H Cai, R Garrepalli, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 7 | 2023 |
| Mamo: Leveraging memory and attention for monocular video depth estimation R Yasarla, H Cai, J Jeong, Y Shi, R Garrepalli, F Porikli Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 6 | 2023 |
| Transadapt: A transformative framework for online test time adaptive semantic segmentation D Das, S Borse, H Park, K Azarian, H Cai, R Garrepalli, F Porikli ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 5 | 2023 |
| Dift: Dynamic iterative field transforms for memory efficient optical flow R Garrepalli, J Jeong, RC Ravindran, JM Lin, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 5 | 2023 |
| Oracle analysis of representations for deep open set detection R Garrepalli arXiv preprint arXiv:2209.11350, 2022 | 4 | 2022 |
| Futuredepth: Learning to predict the future improves video depth estimation R Yasarla, MK Singh, H Cai, Y Shi, J Jeong, Y Zhu, S Han, R Garrepalli, ... arXiv preprint arXiv:2403.12953, 2024 | 2 | 2024 |
| Panoptic segmentation with panoptic, instance, and semantic relations SM Borse, H Park, H Cai, DAS Debasmit, R Garrepalli, FM Porikli US Patent App. 17/807,614, 2023 | 2 | 2023 |
| Can We Achieve Open Category Detection with Guarantees? S Liu, R Garrepalli, A Fern, TG Dietterich Workshops at the Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 2 | 2018 |
| Sparse High Rank Adapters K Bhardwaj, NP Pandey, S Priyadarshi, V Ganapathy, R Esteves, ... arXiv preprint arXiv:2406.13175, 2024 | 1 | 2024 |
| Ocai: Improving optical flow estimation by occlusion and consistency aware interpolation J Jeong, H Cai, R Garrepalli, JM Lin, M Hayat, F Porikli Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
| Clockwork Diffusion: Efficient Generation With Model-Step Distillation A Habibian, A Ghodrati, N Fathima, G Sautiere, R Garrepalli, F Porikli, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
| Vectorized bilinear shift for replacing grid sampling in optical flow estimation R Chockalingapuramravindran, K Urquhart, JM Lin, R Garrepalli US Patent 12,039,740, 2024 | | 2024 |
| FouRA: Fourier Low Rank Adaptation S Borse, S Kadambi, NP Pandey, K Bhardwaj, V Ganapathy, ... arXiv preprint arXiv:2406.08798, 2024 | | 2024 |
| Dynamic delta transformations for segmentation SM Borse, H Park, R Garrepalli, DAS Debasmit, H Cai, FM Porikli US Patent App. 18/346,470, 2024 | | 2024 |
| Regenerative learning to enhance dense prediction SM Borse, DAS Debasmit, H Park, H Cai, R Garrepalli, FM Porikli US Patent App. 18/460,903, 2024 | | 2024 |
| Realistic distraction and pseudo-labeling regularization for optical flow estimation J Jeong, R Garrepalli, H Cai, FM Porikli US Patent App. 18/477,493, 2024 | | 2024 |
Fatih PorikliQualcomm, Australian National UniversityVerified email at anu.edu.au
