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i2c-net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation

Research article (IEEE Robotics and Automation Letters, 2023) · cited 28× · AI/ML
academia openalex:W4320002827
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i2c-net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation

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i2c-net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). i2c-net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation. Retrieved May 24, 2026, from https://4ort.xyz/entity/i2c-net-using-instance-level-neural-networks-for-monocular-category-level-6d-pose-estimation
MLA “i2c-net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/i2c-net-using-instance-level-neural-networks-for-monocular-category-level-6d-pose-estimation.
BibTeX @misc{4ortxyz_i2c-net-using-instance-level-neural-networks-for-monocular-category-level-6d-pose-estimation_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{i2c-net: Using Instance-Level Neural Networks for Monocular Category-Level 6D Pose Estimation}}, year = {2026}, url = {https://4ort.xyz/entity/i2c-net-using-instance-level-neural-networks-for-monocular-category-level-6d-pose-estimation}, note = {Accessed: 2026-05-24}}
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