Bi-directional cross-modality feature propagation with separation-and-aggregation gate for RGB-D semantic segmentation
Depth information has proven to be a useful cue in the semantic segmentation of RGB-D
images for providing a geometric counterpart to the RGB representation. Most existing works …
images for providing a geometric counterpart to the RGB representation. Most existing works …
Efficient rgb-d semantic segmentation for indoor scene analysis
D Seichter, M Köhler, B Lewandowski… - … on robotics and …, 2021 - ieeexplore.ieee.org
Analyzing scenes thoroughly is crucial for mobile robots acting in different environments.
Semantic segmentation can enhance various subsequent tasks, such as (semantically …
Semantic segmentation can enhance various subsequent tasks, such as (semantically …
A brief survey on RGB-D semantic segmentation using deep learning
Semantic segmentation is referred to as a process of linking each pixel in an image to a
class label. With this pragmatic technique, it is possible to recognize different objects in an …
class label. With this pragmatic technique, it is possible to recognize different objects in an …
On 3d reconstruction using rgb-d cameras
The representation of the physical world is an issue that concerns the scientific community
studying computer vision, more and more. Recently, research has focused on modern …
studying computer vision, more and more. Recently, research has focused on modern …
Kidney tumor segmentation from computed tomography images using DeepLabv3+ 2.5 D model
Kidney cancer is a public health problem that affects thousands of people worldwide.
Accurate kidney tumor segmentation is an important task that helps doctors to reduce the …
Accurate kidney tumor segmentation is an important task that helps doctors to reduce the …
Joint implicit image function for guided depth super-resolution
Guided depth super-resolution is a practical task where a low-resolution and noisy input
depth map is restored to a high-resolution version, with the help of a high-resolution RGB …
depth map is restored to a high-resolution version, with the help of a high-resolution RGB …
A closer look at invariances in self-supervised pre-training for 3d vision
L Li, M Heizmann - European conference on computer vision, 2022 - Springer
Self-supervised pre-training for 3D vision has drawn increasing research interest in recent
years. In order to learn informative representations, a lot of previous works exploit …
years. In order to learn informative representations, a lot of previous works exploit …
UCTNet: Uncertainty-aware cross-modal transformer network for indoor RGB-D semantic segmentation
In this paper, we tackle the problem of RGB-D Semantic Segmentation. The key challenges
in solving this problem lie in 1) how to extract features from depth sensor data and 2) how to …
in solving this problem lie in 1) how to extract features from depth sensor data and 2) how to …
Malleable 2.5 D convolution: Learning receptive fields along the depth-axis for RGB-D scene parsing
Depth data provide geometric information that can bring progress in RGB-D scene parsing
tasks. Several recent works propose RGB-D convolution operators that construct receptive …
tasks. Several recent works propose RGB-D convolution operators that construct receptive …
Not all voxels are equal: Semantic scene completion from the point-voxel perspective
Abstract We revisit Semantic Scene Completion (SSC), a useful task to predict the semantic
and occupancy representation of 3D scenes, in this paper. A number of methods for this task …
and occupancy representation of 3D scenes, in this paper. A number of methods for this task …