3 accepted papers
Indoor monocular semantic scene completion (MSSC) is notably more challenging than its outdoor counterpart due to complex spatial layouts and severe occlusions. While transformers are well suited for modeling global dependencies, their high memory cost and difficulty in reconstructing fine-grained d
Monocular Semantic Scene Completion (MSSC) aims to predict the voxel-wise occupancy and semantic category from a single-view RGB image. Existing methods adopt a single-stage framework that aims to simultaneously achieve visible region segmentation and occluded region hallucination, while also being…
As the general description of relationships between attributes, approximate functional dependencies (AFDs) almost hold for a given dataset with a few violations. Most of existing methods for AFD discover are insufficient to balance the efficiency and accuracy due to the massive search space and perm