Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
A brief survey on semantic segmentation with deep learning
S Hao, Y Zhou, Y Guo - Neurocomputing, 2020 - Elsevier
Semantic segmentation is a challenging task in computer vision. In recent years, the
performance of semantic segmentation has been greatly improved by using deep learning …
performance of semantic segmentation has been greatly improved by using deep learning …
Segment anything in 3d with nerfs
Abstract Recently, the Segment Anything Model (SAM) emerged as a powerful vision
foundation model which is capable to segment anything in 2D images. This paper aims to …
foundation model which is capable to segment anything in 2D images. This paper aims to …
Binsformer: Revisiting adaptive bins for monocular depth estimation
Monocular depth estimation (MDE) is a fundamental task in computer vision and has drawn
increasing attention. Recently, some methods reformulate it as a classification-regression …
increasing attention. Recently, some methods reformulate it as a classification-regression …
GMNet: Graded-feature multilabel-learning network for RGB-thermal urban scene semantic segmentation
Semantic segmentation is a fundamental task in computer vision, and it has various
applications in fields such as robotic sensing, video surveillance, and autonomous driving. A …
applications in fields such as robotic sensing, video surveillance, and autonomous driving. A …
Sparse fuse dense: Towards high quality 3d detection with depth completion
Current LiDAR-only 3D detection methods inevitably suffer from the sparsity of point clouds.
Many multi-modal methods are proposed to alleviate this issue, while different …
Many multi-modal methods are proposed to alleviate this issue, while different …
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 …
Visual transformers: Token-based image representation and processing for computer vision
Computer vision has achieved remarkable success by (a) representing images as uniformly-
arranged pixel arrays and (b) convolving highly-localized features. However, convolutions …
arranged pixel arrays and (b) convolving highly-localized features. However, convolutions …
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 …
Deep learning for image super-resolution: A survey
Image Super-Resolution (SR) is an important class of image processing techniqueso
enhance the resolution of images and videos in computer vision. Recent years have …
enhance the resolution of images and videos in computer vision. Recent years have …