| Examining the impact of blur on recognition by convolutional networks I Vasiljevic, A Chakrabarti, G Shakhnarovich arXiv preprint arXiv:1611.05760, 2016 | 258 | 2016 |
| Diode: A dense indoor and outdoor depth dataset I Vasiljevic, N Kolkin, S Zhang, R Luo, H Wang, FZ Dai, AF Daniele, ... arXiv preprint arXiv:1908.00463, 2019 | 241 | 2019 |
| Datacomp-lm: In search of the next generation of training sets for language models J Li, A Fang, G Smyrnis, M Ivgi, M Jordan, SY Gadre, H Bansal, E Guha, ... Advances in Neural Information Processing Systems 37, 14200-14282, 2024 | 93* | 2024 |
| Towards zero-shot scale-aware monocular depth estimation V Guizilini, I Vasiljevic, D Chen, R Ambruș, A Gaidon Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 67 | 2023 |
| Full surround monodepth from multiple cameras V Guizilini, I Vasiljevic, R Ambrus, G Shakhnarovich, A Gaidon IEEE Robotics and Automation Letters 7 (2), 5397-5404, 2022 | 57 | 2022 |
| Neural ray surfaces for self-supervised learning of depth and ego-motion I Vasiljevic, V Guizilini, R Ambrus, S Pillai, W Burgard, G Shakhnarovich, ... 2020 International Conference on 3D Vision (3DV), 1-11, 2020 | 33 | 2020 |
| Self-supervised camera self-calibration from video J Fang, I Vasiljevic, V Guizilini, R Ambrus, G Shakhnarovich, A Gaidon, ... 2022 International Conference on Robotics and Automation (ICRA), 8468-8475, 2022 | 28 | 2022 |
| Language models scale reliably with over-training and on downstream tasks SY Gadre, G Smyrnis, V Shankar, S Gururangan, M Wortsman, R Shao, ... arXiv preprint arXiv:2403.08540, 2024 | 27 | 2024 |
| Depth field networks for generalizable multi-view scene representation V Guizilini, I Vasiljevic, J Fang, R Ambru, G Shakhnarovich, MR Walter, ... European Conference on Computer Vision, 245-262, 2022 | 16 | 2022 |
| Linearizing large language models J Mercat, I Vasiljevic, S Keh, K Arora, A Dave, A Gaidon, T Kollar arXiv preprint arXiv:2405.06640, 2024 | 15 | 2024 |
| Systems and methods for semi-supervised depth estimation according to an arbitrary camera V Guizilini, I Vasiljevic, RA Ambrus, S Pillai, AD Gaidon US Patent 11,436,743, 2022 | 10 | 2022 |
| Systems and methods for self-supervised depth estimation V Guizilini, I Vasiljevic, RA Ambrus, A Gaidon US Patent 11,494,927, 2022 | 6 | 2022 |
| Systems and methods for multi-camera modeling with neural camera networks V Guizilini, I Vasiljevic, RA Ambrus, A Gaidon US Patent 11,321,862, 2022 | 6 | 2022 |
| Examining the impact of blur on recognition by convolutional networks. arXiv 2016 I Vasiljevic, A Chakrabarti, G Shakhnarovich arXiv preprint arXiv:1611.05760, 0 | 6 | |
| Transcrib3d: 3d referring expression resolution through large language models J Fang, X Tan, S Lin, I Vasiljevic, V Guizilini, H Mei, R Ambrus, ... 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2024 | 4 | 2024 |
| Robust self-supervised extrinsic self-calibration T Kanai, I Vasiljevic, V Guizilini, A Gaidon, R Ambrus 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2023 | 4 | 2023 |
| Nerfuser: Large-scale scene representation by nerf fusion J Fang, S Lin, I Vasiljevic, V Guizilini, R Ambrus, A Gaidon, ... arXiv preprint arXiv:2305.13307, 2023 | 4 | 2023 |
| Camera agnostic depth network V Guizilini, S Pillai, AD Gaidon, RA Ambrus, I Vasiljevic US Patent 11,257,231, 2022 | 4 | 2022 |
| Dense depth for autonomous driving (DDAD) challenge A Gaidon, G Shakhnarovich, R Ambrus, V Guizilini, I Vasiljevic, M Walter, ... | 4 | 2021 |
| System and method to improve multi-camera monocular depth estimation using pose averaging V Guizilini, RA Ambrus, AD Gaidon, I Vasiljevic, G Shakhnarovich US Patent 11,727,589, 2023 | 3 | 2023 |
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