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Zhou et al., 2023 - Google Patents

Deep fusion transformer network with weighted vector-wise keypoints voting for robust 6d object pose estimation

Zhou et al., 2023

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Document ID
7060722434837826813
Author
Zhou J
Chen K
Xu L
Dou Q
Qin J
Publication year
Publication venue
Proceedings of the IEEE/CVF International Conference on Computer Vision

External Links

Snippet

One critical challenge in 6D object pose estimation from a single RGBD image is efficient integration of two different modalities, ie, color and depth. In this work, we tackle this problem by a novel Deep Fusion Transformer (DFTr) block that can aggregate cross-modality …
Continue reading at openaccess.thecvf.com (PDF) (other versions)

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    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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