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 …
DBCNet: Dynamic bilateral cross-fusion network for RGB-T urban scene understanding in intelligent vehicles
Understanding urban scenes is a fundamental capability required of intelligent vehicles.
Depth cues provide useful geometric information for semantic segmentation, thus …
Depth cues provide useful geometric information for semantic segmentation, thus …
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 …
Global contextually guided lightweight network for RGB-thermal urban scene understanding
Recent achievements in scene understanding have benefited considerably from the rapid
development of convolutional neural networks. However, improvements of scene …
development of convolutional neural networks. However, improvements of scene …
Non-local aggregation for RGB-D semantic segmentation
Exploiting both RGB (2D appearance) and Depth (3D geometry) information can improve
the performance of semantic segmentation. However, due to the inherent difference …
the performance of semantic segmentation. However, due to the inherent difference …
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 …
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 …