Guided depth map super-resolution: A survey
Guided depth map super-resolution (GDSR), which aims to reconstruct a high-resolution
depth map from a low-resolution observation with the help of a paired high-resolution color …
depth map from a low-resolution observation with the help of a paired high-resolution color …
[HTML][HTML] Multimodal semantic segmentation in autonomous driving: A review of current approaches and future perspectives
The perception of the surrounding environment is a key requirement for autonomous driving
systems, yet the computation of an accurate semantic representation of the scene starting …
systems, yet the computation of an accurate semantic representation of the scene starting …
Omnivore: A single model for many visual modalities
Prior work has studied different visual modalities in isolation and developed separate
architectures for recognition of images, videos, and 3D data. Instead, in this paper, we …
architectures for recognition of images, videos, and 3D data. Instead, in this paper, we …
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 …
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 …
Cross-level feature aggregation network for polyp segmentation
Accurate segmentation of polyps from colonoscopy images plays a critical role in the
diagnosis and cure of colorectal cancer. Although effectiveness has been achieved in the …
diagnosis and cure of colorectal cancer. Although effectiveness has been achieved in the …
Delivering arbitrary-modal semantic segmentation
Multimodal fusion can make semantic segmentation more robust. However, fusing an
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
arbitrary number of modalities remains underexplored. To delve into this problem, we create …
Semantic segmentation for real point cloud scenes via bilateral augmentation and adaptive fusion
Given the prominence of current 3D sensors, a fine-grained analysis on the basic point
cloud data is worthy of further investigation. Particularly, real point cloud scenes can …
cloud data is worthy of further investigation. Particularly, real point cloud scenes can …
Changer: Feature interaction is what you need for change detection
S Fang, K Li, Z Li - IEEE Transactions on Geoscience and …, 2023 - ieeexplore.ieee.org
Change detection is an important tool for long-term Earth observation missions. It takes bi-
temporal images as input and predicts “where” the change has occurred. Different from other …
temporal images as input and predicts “where” the change has occurred. Different from other …
UrbanLF: A comprehensive light field dataset for semantic segmentation of urban scenes
As one of the fundamental technologies for scene understanding, semantic segmentation
has been widely explored in the last few years. Light field cameras encode the geometric …
has been widely explored in the last few years. Light field cameras encode the geometric …