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 …
Understanding deep learning techniques for image segmentation
The machine learning community has been overwhelmed by a plethora of deep learning--
based approaches. Many challenging computer vision tasks, such as detection, localization …
based approaches. Many challenging computer vision tasks, such as detection, localization …
Decomposing nerf for editing via feature field distillation
S Kobayashi, E Matsumoto… - Advances in Neural …, 2022 - proceedings.neurips.cc
Emerging neural radiance fields (NeRF) are a promising scene representation for computer
graphics, enabling high-quality 3D reconstruction and novel view synthesis from image …
graphics, enabling high-quality 3D reconstruction and novel view synthesis from image …
Language-driven semantic segmentation
We present LSeg, a novel model for language-driven semantic image segmentation. LSeg
uses a text encoder to compute embeddings of descriptive input labels (eg," grass" or" …
uses a text encoder to compute embeddings of descriptive input labels (eg," grass" or" …
SHIFT: a synthetic driving dataset for continuous multi-task domain adaptation
Adapting to a continuously evolving environment is a safety-critical challenge inevitably
faced by all autonomous-driving systems. Existing image-and video-based driving datasets …
faced by all autonomous-driving systems. Existing image-and video-based driving datasets …
Semantic segmentation using Vision Transformers: A survey
H Thisanke, C Deshan, K Chamith… - … Applications of Artificial …, 2023 - Elsevier
Semantic segmentation has a broad range of applications in a variety of domains including
land coverage analysis, autonomous driving, and medical image analysis. Convolutional …
land coverage analysis, autonomous driving, and medical image analysis. Convolutional …
Eff-unet: A novel architecture for semantic segmentation in unstructured environment
Since the last few decades, the number of road causalities has seen continuous growth
across the globe. Nowadays intelligent transportation systems are being developed to …
across the globe. Nowadays intelligent transportation systems are being developed to …
Efficientps: Efficient panoptic segmentation
Understanding the scene in which an autonomous robot operates is critical for its competent
functioning. Such scene comprehension necessitates recognizing instances of traffic …
functioning. Such scene comprehension necessitates recognizing instances of traffic …
Generative semantic segmentation
Abstract We present Generative Semantic Segmentation (GSS), a generative learning
approach for semantic segmentation. Uniquely, we cast semantic segmentation as an image …
approach for semantic segmentation. Uniquely, we cast semantic segmentation as an image …
A survey on deep learning-based architectures for semantic segmentation on 2d images
I Ulku, E Akagündüz - Applied Artificial Intelligence, 2022 - Taylor & Francis
Semantic segmentation is the pixel-wise labeling of an image. Boosted by the extraordinary
ability of convolutional neural networks (CNN) in creating semantic, high-level and …
ability of convolutional neural networks (CNN) in creating semantic, high-level and …