Artikel dengan mandat akses publik - Derek HoiemPelajari lebih lanjut
Tidak tersedia di mana pun: 1
Addressing Low-Shot MVS by Detecting and Completing Planar Surfaces
R Kataria, Z Li, J DeGol, D Hoiem
2024 International Conference on 3D Vision (3DV), 549-558, 2024
Mandat: US National Science Foundation
Tersedia di suatu tempat: 29
Learning without forgetting
Z Li, D Hoiem
IEEE transactions on pattern analysis and machine intelligence 40 (12), 2935 …, 2017
Mandat: US National Science Foundation, US Department of Defense
Dreaming to distill: Data-free knowledge transfer via deepinversion
H Yin, P Molchanov, JM Alvarez, Z Li, A Mallya, D Hoiem, NK Jha, J Kautz
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
Mandat: US Department of Defense
Where to look: Focus regions for visual question answering
KJ Shih, S Singh, D Hoiem
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Mandat: US National Science Foundation
Layoutnet: Reconstructing the 3d room layout from a single rgb image
C Zou, A Colburn, Q Shan, D Hoiem
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Mandat: US National Science Foundation, US Department of Defense
3d-prnn: Generating shape primitives with recurrent neural networks
C Zou, E Yumer, J Yang, D Ceylan, D Hoiem
Proceedings of the IEEE International Conference on Computer Vision, 900-909, 2017
Mandat: US National Science Foundation, US Department of Defense
No-frills human-object interaction detection: Factorization, layout encodings, and training techniques
T Gupta, A Schwing, D Hoiem
Proceedings of the IEEE/CVF international conference on computer vision …, 2019
Mandat: US National Science Foundation, US Department of Defense
Contrastive learning for weakly supervised phrase grounding
T Gupta, A Vahdat, G Chechik, X Yang, J Kautz, D Hoiem
European Conference on Computer Vision, 752-768, 2020
Mandat: US Department of Defense
Pixels, voxels, and views: A study of shape representations for single view 3d object shape prediction
D Shin, CC Fowlkes, D Hoiem
Proceedings of the IEEE conference on computer vision and pattern …, 2018
Mandat: US National Science Foundation, US Department of Defense
Language models with image descriptors are strong few-shot video-language learners
Z Wang, M Li, R Xu, L Zhou, J Lei, X Lin, S Wang, Z Yang, C Zhu, ...
Advances in Neural Information Processing Systems 35, 8483-8497, 2022
Mandat: US Department of Defense
Unified-io 2: Scaling autoregressive multimodal models with vision language audio and action
J Lu, C Clark, S Lee, Z Zhang, S Khosla, R Marten, D Hoiem, A Kembhavi
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
Mandat: US Department of Defense
Chromatag: A colored marker and fast detection algorithm
J DeGol, T Bretl, D Hoiem
Proceedings of the IEEE international conference on computer vision, 1472-1481, 2017
Mandat: US National Science Foundation, US Department of Defense
Towards general purpose vision systems: An end-to-end task-agnostic vision-language architecture
T Gupta, A Kamath, A Kembhavi, D Hoiem
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
Mandat: US Department of Defense
Imagine this! scripts to compositions to videos
T Gupta, D Schwenk, A Farhadi, D Hoiem, A Kembhavi
Proceedings of the European conference on computer vision (ECCV), 598-613, 2018
Mandat: US Department of Defense
Geometry-informed material recognition
J DeGol, M Golparvar-Fard, D Hoiem
Proceedings of the IEEE conference on computer vision and pattern …, 2016
Mandat: US National Science Foundation
Webly supervised concept expansion for general purpose vision models
A Kamath, C Clark, T Gupta, E Kolve, D Hoiem, A Kembhavi
European Conference on Computer Vision, 662-681, 2022
Mandat: US Department of Defense
Manhattan Room Layout Reconstruction from a Single Image: A Comparative Study of State-of-the-Art Methods
C Zou, JW Su, CH Peng, A Colburn, Q Shan, P Wonka, HK Chu, D Hoiem
International Journal of Computer Vision 129, 1410-1431, 2021
Mandat: US Department of Defense
Improving confidence estimates for unfamiliar examples
Z Li, D Hoiem
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
Mandat: US National Science Foundation, US Department of Defense
Improved structure from motion using fiducial marker matching
J DeGol, T Bretl, D Hoiem
Proceedings of the European Conference on Computer Vision (ECCV), 273-288, 2018
Mandat: US National Science Foundation, US Department of Defense
Vico: Word embeddings from visual co-occurrences
T Gupta, A Schwing, D Hoiem
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019
Mandat: US National Science Foundation, US Department of Defense
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