Search Results for author:
Found 5 papers, 1 papers with code
HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness
In this paper, from a new perspective, we propose a novel Hierarchical Depth Awareness network (HiDAnet) for RGB-D saliency detection.
Robust RGB-D Fusion for Saliency Detection
In this work, we aim for RGB-D saliency detection that is robust to the low-quality depths which primarily appear in two forms: inaccuracy due to noise and the misalignment to RGB.
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.
Ranked #41 on
Semantic Segmentation
on NYU Depth v2
Modality-Guided Subnetwork for Salient Object Detection
Recent RGBD-based models for saliency detection have attracted research attention.
Depth-Adapted CNN for RGB-D cameras
These filters compute the spatial coherence by weighting the photometric information on a fixed neighborhood without taking into account the geometric information.
