Obserwuj
Igor Vasiljevic
Igor Vasiljevic
Toyota Research Institute (TRI)
Zweryfikowany adres z ttic.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Examining the impact of blur on recognition by convolutional networks
I Vasiljevic, A Chakrabarti, G Shakhnarovich
arXiv preprint arXiv:1611.05760, 2016
2312016
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
1602019
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
372022
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
232020
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
162022
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
132023
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
122022
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
62022
Systems and methods for self-supervised depth estimation
V Guizilini, I Vasiljevic, RA Ambrus, A Gaidon
US Patent 11,494,927, 2022
42022
Camera agnostic depth network
V Guizilini, S Pillai, AD Gaidon, RA Ambrus, I Vasiljevic
US Patent 11,257,231, 2022
42022
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
32023
Systems and methods for self-supervised depth estimation according to an arbitrary camera
V Guizilini, I Vasiljevic, RA Ambrus, S Pillai, AD Gaidon
US Patent 11,652,972, 2023
22023
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
22022
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
12023
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
12023
Systems and methods for self-supervised learning of camera intrinsic parameters from a sequence of images
V Guizilini, AD Gaidon, RA Ambrus, I Vasiljevic, J Fang, G Shakhnarovich, ...
US Patent App. 17/692,357, 2023
12023
Scale-aware depth estimation using multi-camera projection loss
V Guizilini, RA Ambrus, AD Gaidon, I Vasiljevic, G Shakhnarovich
US Patent App. 17/390,760, 2022
12022
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
2024
Language models scale reliably with over-training and on downstream tasks
S Yitzhak Gadre, G Smyrnis, V Shankar, S Gururangan, M Wortsman, ...
arXiv e-prints, arXiv: 2403.08540, 2024
2024
Geometric 3d augmentations for transformer architectures
V Guizilini, I Vasiljevic, AD Gaidon, J Fang, G Shakhnarovich, MR Walter, ...
US Patent App. 18/110,421, 2024
2024
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20