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CMX: Cross-modal fusion for RGB-X semantic segmentation with transformers
Scene understanding based on image segmentation is a crucial component of autonomous
vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting …
vehicles. Pixel-wise semantic segmentation of RGB images can be advanced by exploiting …
Delivering arbitrary-modal semantic segmentation
Multimodal fusion can make semantic segmentation more robust. However, fusing an
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
Source-free depth for object pop-out
Depth cues are known to be useful for visual perception. However, direct measurement of
depth is often impracticable. Fortunately, though, modern learning-based methods offer …
depth is often impracticable. Fortunately, though, modern learning-based methods offer …
Dformer: Rethinking rgbd representation learning for semantic segmentation
Depth-adapted CNNs for RGB-D semantic segmentation
Recent RGB-D semantic segmentation has motivated research interest thanks to the
accessibility of complementary modalities from the input side. Existing works often adopt a …
accessibility of complementary modalities from the input side. Existing works often adopt a …
Modality-guided subnetwork for salient object detection
Recent RGBD-based models for saliency detection have attracted research attention. The
depth clues such as boundary clues, surface normal, shape attribute, etc., contribute to the …
depth clues such as boundary clues, surface normal, shape attribute, etc., contribute to the …