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We present Visual-Language Fields (VL-Fields), a neural implicit spatial representation that enables open-vocabulary semantic queries.
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L. Mescheder, M. Oechsle and M. Niemeyer and S. Nowozin and A. Geiger, “Occupancy Networks: Learning 3D Reconstruction in Function Space,” in Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR)
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J. J. Park, P. Florence, J. Straub, R. Newcombe, and S. Lovegrove, “DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation,” in the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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E. Sucar, S. Liu, J. Ortiz, and A. J. Davison, “iMAP: Implicit mapping and positioning in real-time,” in Proceedings of the International Conference on Computer Vision (ICCV)
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S. Zhi, T. Laidlow, S. Leutenegger, and A. J. Davison, “In-place scene labelling and understanding with implicit scene representation,” in Proceedings of the International Conference on Computer Vision (ICCV)
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B. Li, K. Q. Weinberger, S. Belongie, V. Koltun and R. Ranftl, “Language-driven semantic segmentation,” in International Conference on Learning Representations
2021
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Z. Li, S. Niklaus, N. Snavely, and O. Wang, “Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2021
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L. Yen-Chen, P. Florence, J. T. Barron, A. Rodriguez, P. Isola, and T. Lin, “iNeRF: Inverting Neural Radiance Fields for Pose Estimation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2021
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2021
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V. Tschernezki and I. Laina and D. Larlus and A. Vedaldi, ”Neural Feature Fusion Fields: 3D Distillation of Self-Supervised 2D Image Representations,” in Proc. of Joint 3DIM/3DPVT Conference (3DV)
2022
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I. Haughton, E. Sucar, A. Mouton, E. Johns and A. Davison, “Real-time Mapping of Physical Scene Properties with an Autonomous Robot Experimenter,” in 6th Annual Conference on Robot Learning (CoRL)
2022
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A. Simeonov, Y. Du, A. Tagliasacchi, J. B. Tenenbaum, A. Rodriguez, P. Agrawal, and V. Sitzmann, “Neural descriptor fields: Se(3)-equivariant object representations for manipulation,” in 2022 International Conference on Robotics and Automation (ICRA)
2022
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S. Vora, N. Radwan, K. Greff, H. Meyer, K. Genova, M. S. M. Sajjadi, et al. , “NeSF: Neural semantic fields for generalizable semantic segmentation of 3d scenes,” in Transactions on Machine Learning Research (TMLR)
2022
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K. Rematas, A. Liu, P. P. Srinivasan, J. T. Barron, A. Tagliasacchi, T. Funkhouser, and V. Ferrari, “Urban Radiance Fields,” in Computer Vision and Pattern Recognition (CVPR)
2022
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2022
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2022
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T. Muller, A. Evans, C. Schied, and A. Keller, “Instant neural graphics primitives with a multiresolution hash encoding,” in Proceedings of SIGGRAPH
2022
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G. Ghiasi, X. Gu, Y. Cui, and T. Lin, “Scaling Open-Vocabulary Image Segmentation With Image-Level Labels,” in European Conference on Computer Vision (ECCV)
2022
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N. M. M. Shafiullah, C. Paxton, L. Pinto, S. Chintala and A. Szlam, “CLIP-fields: Weakly supervised semantic fields for robotic memory” in Workshop on Language and Robotics at CoRL 2022
2022
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2022
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Z. Zhu, S. Peng, V. Larsson, W. Xu, H. Bao, Z. Cui, M. Oswald and M. Pollefeys, “NICE-SLAM: Neural Implicit Scalable Encoding for SLAM,”, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
2022
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2022
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Y. Xie, T. Takikawa, S. Saito, O. Litany, S. Yan, N. Khan, et al. , “Neural Fields in Visual Computing and Beyond,” in Computer Graphics Forum
2022
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X. Zhou, R. Girdhar, A. Joulin, P. Krähenbühl, and I. Misra, “Detecting twenty-thousand classes using image-level supervision,” in European Conference on Computer Vision (ECCV)
2022
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X. Li, S. De Mello, X. Wang, M. Yang, J. Kautz, and S. Liu, “Learning Continuous Environment Fields via Implicit Functions,” in International Conference on Learning Representations (ICLR)
2022
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A. Simeonov, Y. Du, A. Tagliasacchi, J. B. Tenenbaum, A. Rodriguez, P. Agrawal, and V. Sitzmann, “Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation,” in International Conference on Robotics and Automation (ICRA)
2022
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S. Kobayashi, E. Matsumoto, and V. Sitzmann, “Decomposing nerf for editing via feature field distillation,” in Advances in Neural Information Processing Systems , 2022
2022
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K. Mazur, E. Sucar, A. Davison, ”Feature-Realistic Neural Fusion for Real-Time, Open Set Scene Understanding,” in International Conference on Robotics and Automation (ICRA)
2023
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S. Peng, K.Genova, C. M. Jiang, A. Tagliasacchi, M. Pollefeys, and T. Funkhouser “OpenScene: 3D Scene Understanding with Open Vocabularies,” in Computer Vision and Pattern Recognition (CVPR)
2023
Closest in time.
2023
Closest in time.
2023
Closest in time.
B. Wang, L. Chen, and B. Yang, “Dm-nerf: 3d scene geometry decomposition and manipulation from 2d images,” in International Conference on Learning Representations (ICLR)
2023
Closest in time.