Adjacent Bi-Hierarchical Network for Scene Parsing of Remote Sensing Images
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2023.3241648
Abstract: Driven by the rapid development and application of earth observation sensors, the scene parsing of remote sensing images (RSIs) has attracted extensive research attention in recent years. Restricted by the limited local receptive field of… read more here.
Keywords: remote sensing; parsing remote; sensing images; adjacent hierarchical ... See more keywords
GEBNet: Graph-Enhancement Branch Network for RGB-T Scene Parsing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3219350
Abstract: RGB-T (red–green–blue and thermal) scene parsing has recently drawn considerable research attention. Although existing methods efficiently conduct RGB-T scene parsing, their performance remains limited by a small receptive field. Unlike methods that capture the global… read more here.
Keywords: enhancement branch; graph; graph enhancement; scene parsing ... See more keywords
CEGFNet: Common Extraction and Gate Fusion Network for Scene Parsing of Remote Sensing Images
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3109626
Abstract: Scene parsing of high spatial resolution (HSR) remote sensing images has achieved notable progress in recent years by the adoption of convolutional neural networks. However, for scene parsing of multimodal remote sensing images, effectively integrating… read more here.
Keywords: sensing images; scene parsing; gate fusion; remote sensing ... See more keywords
Multifeature Selective Fusion Network for Real-Time Driving Scene Parsing
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2021.3070611
Abstract: Real-time driving scene parsing using semantic segmentation is an essential yet challenging task for an autonomous driving system, where both efficiency and accuracy need to be considered simultaneously. In this article, we propose an efficient… read more here.
Keywords: selective fusion; real time; driving scene; scene parsing ... See more keywords
ORDNet: Capturing Omni-Range Dependencies for Scene Parsing
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2020.3013142
Abstract: Learning to capture dependencies between spatial positions is essential to many visual tasks, especially the dense labeling problems like scene parsing. Existing methods can effectively capture long-range dependencies with self-attention mechanism while short ones by… read more here.
Keywords: ordnet; range; omni range; long range ... See more keywords
Nighttime Road Scene Parsing by Unsupervised Domain Adaptation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2020.3033569
Abstract: Due to recent advances in learning-based semantic segmentation, road scene parsing can usually achieve satisfactory results under normal illumination conditions. However, training a robust model for parsing nighttime road scenes is still very challenging, especially… read more here.
Keywords: segmentation; scene parsing; nighttime road; road ... See more keywords
Fully Decoupled Residual ConvNet for Real-Time Railway Scene Parsing of UAV Aerial Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2021.3134318
Abstract: UAV-based automatic railway inspection is expected to have the potential to reform the inspection of railways. In this area, real-time railway scene parsing is quite essential. However, the limited computation resources of the UAV onboard… read more here.
Keywords: railway; decoupled residual; fully decoupled; real time ... See more keywords
MFFENet: Multiscale Feature Fusion and Enhancement Network For RGB–Thermal Urban Road Scene Parsing
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2021.3086618
Abstract: Compared with traditional handcrafted features, deep learning has greatly improved the performance of scene parsing. However, it remains challenging under various environmental conditions caused by imaging limitations. Thermal imaging cameras have several advantages over cameras… read more here.
Keywords: fusion; feature fusion; rgb; rgb thermal ... See more keywords
Perspective-Adaptive Convolutions for Scene Parsing
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2018.2890637
Abstract: Many existing scene parsing methods adopt Convolutional Neural Networks with receptive fields of fixed sizes and shapes, which frequently results in inconsistent predictions of large objects and invisibility of small objects. To tackle this issue,… read more here.
Keywords: convolutions scene; perspective adaptive; receptive fields; adaptive convolutions ... See more keywords
Temporal Pixel-Level Semantic Understanding Through the VSPW Dataset.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2023.3266023
Abstract: Scene understanding through pixel-level semantic parsing is one of the main problems in computer vision. Till now, image-based methods and datasets for scene parsing have been well explored. However, the real world is naturally dynamic… read more here.
Keywords: pixel level; video scene; level semantic; scene parsing ... See more keywords
FASFLNet: feature adaptive selection and fusion lightweight network for RGB-D indoor scene parsing.
Sign Up to like & getrecommendations! Published in 2023 at "Optics express"
DOI: 10.1364/oe.480252
Abstract: RGB-D indoor scene parsing is a challenging task in computer vision. Conventional scene-parsing approaches based on manual feature extraction have proved inadequate in this area because indoor scenes are both unordered and complex. This study… read more here.
Keywords: indoor scene; rgb indoor; rgb; feature ... See more keywords