| Statler: State-maintaining language models for embodied reasoning T Yoneda, J Fang, P Li, H Zhang, T Jiang, S Lin, B Picker, D Yunis, H Mei, ... 2024 IEEE International Conference on Robotics and Automation (ICRA), 15083 …, 2024 | 37 | 2024 |
| 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 |
| 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 |
| 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 |
| 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 |
| Mango: A benchmark for evaluating mapping and navigation abilities of large language models P Ding, J Fang, P Li, K Wang, X Zhou, M Yu, J Li, MR Walter, H Mei arXiv preprint arXiv:2403.19913, 2024 | 3 | 2024 |
| Delira: Self-supervised depth, light, and radiance fields V Guizilini, I Vasiljevic, J Fang, R Ambrus, S Zakharov, V Sitzmann, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 3 | 2023 |
| Transcribe3d: Grounding llms using transcribed information for 3d referential reasoning with self-corrected finetuning J Fang, X Tan, S Lin, H Mei, M Walter 2nd Workshop on Language and Robot Learning: Language as Grounding, 2023 | 2 | 2023 |
| 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 12,175,708, 2024 | 1 | 2024 |
| Fusing neural radiance fields by registration and blending J Fang, LIN Shengjie, I Vasiljevic, VC Guizilini, RA Ambrus, AD Gaidon, ... US Patent App. 18/429,137, 2024 | | 2024 |
| Systems and methods for generating an image using interpolation of features J Fang, V Guizilini, I Vasiljevic, RA Ambrus, G Shakhnarovich, MR Walter, ... US Patent App. 18/127,949, 2024 | | 2024 |
| Systems and methods for depth synthesis with transformer architectures V Guizilini, I Vasiljevic, AD Gaidon, G Shakhnarovich, M Walter, J Fang, ... US Patent App. 18/156,958, 2024 | | 2024 |
| Radiant and volumetric latent space encoding for volumetric rendering V Guizilini, RA Ambrus, J Fang, S Zakharov, V Sitzmann, I Vasiljevic, ... US Patent App. 18/364,946, 2024 | | 2024 |
| Cross-attention decoding for volumetric rendering V Guizilini, RA Ambrus, J Fang, S Zakharov, V Sitzmann, I Vasiljevic, ... US Patent App. 18/364,783, 2024 | | 2024 |
| Shared latent spaces for volumetric rendering V Guizilini, RA Ambrus, J Fang, S Zakharov, V Sitzmann, I Vasiljevic, ... US Patent App. 18/364,922, 2024 | | 2024 |
| Self-supervised depth for volumetric rendering regularization V Guizilini, RA Ambrus, J Fang, S Zakharov, V Sitzmann, I Vasiljevic, ... US Patent App. 18/364,853, 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 |
Matthew R. WalterToyota Technological Institute at Chicagoبريد إلكتروني تم التحقق منه على ttic.edu