Review the state-of-the-art technologies of semantic segmentation based on deep learning
The goal of semantic segmentation is to segment the input image according to semantic
information and predict the semantic category of each pixel from a given label set. With the …
information and predict the semantic category of each pixel from a given label set. With the …
Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …
order to achieve robust and accurate scene understanding, autonomous vehicles are …
Deep multimodal fusion for semantic image segmentation: A survey
Recent advances in deep learning have shown excellent performance in various scene
understanding tasks. However, in some complex environments or under challenging …
understanding tasks. However, in some complex environments or under challenging …
Self-supervised model adaptation for multimodal semantic segmentation
Learning to reliably perceive and understand the scene is an integral enabler for robots to
operate in the real-world. This problem is inherently challenging due to the multitude of …
operate in the real-world. This problem is inherently challenging due to the multitude of …
Multimodal end-to-end autonomous driving
A crucial component of an autonomous vehicle (AV) is the artificial intelligence (AI) is able to
drive towards a desired destination. Today, there are different paradigms addressing the …
drive towards a desired destination. Today, there are different paradigms addressing the …
Real-time fusion network for RGB-D semantic segmentation incorporating unexpected obstacle detection for road-driving images
Semantic segmentation has made striking progress due to the success of deep
convolutional neural networks. Considering the demands of autonomous driving, real-time …
convolutional neural networks. Considering the demands of autonomous driving, real-time …
Semantic image segmentation: Two decades of research
Semantic image segmentation (SiS) plays a fundamental role in a broad variety of computer
vision applications, providing key information for the global understanding of an image. This …
vision applications, providing key information for the global understanding of an image. This …
Indoor scene understanding in 2.5/3d for autonomous agents: A survey
With the availability of low-cost and compact 2.5/3D visual sensing devices, computer vision
community is experiencing a growing interest in visual scene understanding of indoor …
community is experiencing a growing interest in visual scene understanding of indoor …
End-to-end real-time obstacle detection network for safe self-driving via multi-task learning
Semantic segmentation and depth estimation lie at the heart of scene understanding and
play crucial roles especially for autonomous driving. In particular, it is desirable for an …
play crucial roles especially for autonomous driving. In particular, it is desirable for an …
Advance generalization technique through 3D CNN to overcome the false positives pedestrian in autonomous vehicles
With the popularity of autonomous vehicles and the rapid development of intelligent
transportation, the application scenarios for detecting pedestrians in everyday life are …
transportation, the application scenarios for detecting pedestrians in everyday life are …