4 accepted papers
This paper proposes a multi-view collaborative matching strategy for reliable track construction in complex scenarios. We observe that the pairwise matching paradigms applied to image set matching often result in ambiguous estimation when the selected independent pairs exhibit significant occlusions…
Due to the irregular and disordered data structure in 3D point clouds, prior works have focused on designing more sophisticated local representation methods to capture these complex local patterns. However, the recognition performance has saturated over the past few years, indicating that increasing…
"This paper proposes a side-view context inpainting strategy (SidePaint) to ease the reasoning of unknown 3D patterns for semantic scene completion. Based on the observation that the learning burden on pattern completion increases with spatial complexity and feature sparsity, the SidePaint strategy…
This paper proposes a shape anchor guided learning strategy (AncLearn) for robust holistic indoor scene understanding. We observe that the search space constructed by current methods for proposal feature grouping and instance point sampling often introduces massive noise to instance detection and me…