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Lrru: Long-short range recurrent updating networks for depth completion
Existing deep learning-based depth completion methods generally employ massive stacked
layers to predict the dense depth map from sparse input data. Although such approaches …
layers to predict the dense depth map from sparse input data. Although such approaches …
Recent advances in conventional and deep learning-based depth completion: A survey
Z ** baseline
Transparent objects are common in our daily life and frequently handled in the automated
production line. Robust vision-based robotic gras** and manipulation for these objects …
production line. Robust vision-based robotic gras** and manipulation for these objects …
Aggregating feature point cloud for depth completion
Guided depth completion aims to recover dense depth maps by propagating depth
information from the given pixels to the remaining ones under the guidance of RGB images …
information from the given pixels to the remaining ones under the guidance of RGB images …
SemAttNet: Toward attention-based semantic aware guided depth completion
Depth completion involves recovering a dense depth map from a sparse map and an RGB
image. Recent approaches focus on utilizing color images as guidance images to recover …
image. Recent approaches focus on utilizing color images as guidance images to recover …
[HTML][HTML] A critical review of deep learning-based multi-sensor fusion techniques
B Marsh, AH Sadka, H Bahai - Sensors, 2022 - mdpi.com
In this review, we provide a detailed coverage of multi-sensor fusion techniques that use
RGB stereo images and a sparse LiDAR-projected depth map as input data to output a …
RGB stereo images and a sparse LiDAR-projected depth map as input data to output a …
Towards accurate reconstruction of 3d scene shape from a single monocular image
Despite significant progress made in the past few years, challenges remain for depth
estimation using a single monocular image. First, it is nontrivial to train a metric-depth …
estimation using a single monocular image. First, it is nontrivial to train a metric-depth …
Graphcspn: Geometry-aware depth completion via dynamic gcns
Image guided depth completion aims to recover per-pixel dense depth maps from sparse
depth measurements with the help of aligned color images, which has a wide range of …
depth measurements with the help of aligned color images, which has a wide range of …
Rgb-depth fusion gan for indoor depth completion
The raw depth image captured by the indoor depth sensor usually has an extensive range of
missing depth values due to inherent limitations such as the inability to perceive transparent …
missing depth values due to inherent limitations such as the inability to perceive transparent …