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OCNet: Object Context Network for Scene Parsing
[article]
2021
arXiv
pre-print
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Motivated by the fact that the category of each pixel is inherited from the object it belongs to, we define the object context for each pixel as the set of pixels that belong to the same category as the ...
In this paper, we address the semantic segmentation task with a new context aggregation scheme named object context, which focuses on enhancing the role of object information. ...
PASCAL-Context (Mottaghi et al., 2014 ) is a challenging scene parsing dataset that contains (a) OCNet
BackBone
Object Context Module
Classifier
(b) Base-OC
3x3 Conv
OCP
(c) Pyramid-OC
1x1 ...
arXiv:1809.00916v4
fatcat:h6r25be3hbbbbkcipf4pxea56i
Deep Grouping Model for Unified Perceptual Parsing
[article]
2020
arXiv
pre-print
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When evaluating the model on the recent Broden+ dataset for the unified perceptual parsing task, it achieves state-of-the-art results while having a small computational overhead compared to other contextual-based ...
Examples can be found in the classical hierarchical superpixel segmentation or image parsing works. ...
Similarly, global scene context can also be propagated down to lower-level graph containing objects. ...
arXiv:2003.11647v1
fatcat:bopfoo3hcreztbxmgbjfdktwli
Deep Grouping Model for Unified Perceptual Parsing
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Preserved Fulltext
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When evaluating the model on the recent Broden+ dataset for the unified perceptual parsing task, it achieves state-ofthe-art results while having a small computational overhead compared to other contextual-based ...
Examples can be found in the classical hierarchical superpixel segmentation or image parsing works. ...
Similarly, global scene context can also be propagated down to lower-level graph containing objects. ...
doi:10.1109/cvpr42600.2020.00411
dblp:conf/cvpr/LiBZX20
fatcat:mmcaro5id5axvpquq3auawhyja
Gated Path Selection Network for Semantic Segmentation
[article]
2020
arXiv
pre-print
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In this paper, we develop a novel network named Gated Path Selection Network (GPSNet), which aims to learn adaptive receptive fields. ...
The derived adaptive receptive fields are data-dependent, and are flexible that can model different object geometric transformations. ...
The scene parsing dataset ADE20K contains 150 classes and diverse complex scenes with 1,038 imagelevel categories. It needs to parse both objects and stuff. ...
arXiv:2001.06819v1
fatcat:y6w5amzi4vcyxpa36ttsabbtvq
Deep Multiphase Level Set for Scene Parsing
[article]
2019
arXiv
pre-print
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Recently, Fully Convolutional Network (FCN) seems to be the go-to architecture for image segmentation, including semantic scene parsing. ...
However, it is difficult for a generic FCN to discriminate pixels around the object boundaries, thus FCN based methods may output parsing results with inaccurate boundaries. ...
[32] propose the pyramid object context to model the category dependencies. Fu et al. ...
arXiv:1910.03166v2
fatcat:7viff6ta75hy7fgg5rnxcya2wa
CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:1904.08170v2 fatcat:yuyco2qnurdftkuyst65fmrjzaOther Versions
In this paper, we propose a Content-Adaptive Scale Interaction Network (CASINet) to exploit the multi-scale features for scene parsing. ...
Objects at different spatial positions in an image exhibit different scales. Adaptive receptive fields are expected to capture suitable ranges of context for accurate pixel level semantic prediction. ...
Scene parsing has achieved great progress with the development of Fully Convolutional Networks (FCNs) [11] . ...
arXiv:1904.08170v3
fatcat:rxeulrn225gerdd5mf5mgamqum
Deep Learning Model with GA based Feature Selection and Context Integration
[article]
2022
arXiv
pre-print
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Stanford Background and CamVid benchmark image parsing datasets were used for our model evaluation, and our model shows promising results. ...
Since its inception, Many top-performing methods for image segmentation are based on deep CNN models. ...
Predictive scene parsing models: Spatio-Temporally Coupled Generative Adversarial Networks (STC-GAN) [20] combines a future frame generation model with a predictive scene parsing model. ...
arXiv:2204.06189v1
fatcat:qkyclvhyrzed7lt2cimvylj2ou
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes
[article]
2021
arXiv
pre-print
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Semantic segmentation is a key technology for autonomous vehicles to understand the surrounding scenes. ...
Using light-weight architectures (encoder-decoder or two-pathway) or reasoning on low-resolution images, recent methods realize very fast scene parsing, even running at more than 100 FPS on a single 1080Ti ...
Object Context Network (OCNet) [37] utilizes self-attention mechanism to explore object context which is defined as a set of pixels belonging to the same object category. ...
arXiv:2101.06085v2
fatcat:lzmgglakurb4tkvxlwfkfwx33e
ISNet: Integrate Image-Level and Semantic-Level Context for Semantic Segmentation
[article]
2021
arXiv
pre-print
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First, an image-level context module is designed to capture the contextual information for each pixel in the whole image. ...
Co-occurrent visual pattern makes aggregating contextual information a common paradigm to enhance the pixel representation for semantic image segmentation. ...
Since there are only 9K images in the train set of COCOStuff where these images contain 182 semantic classes, COCOStuff is a very challenging benchmark for scene parsing. ...
arXiv:2108.12382v1
fatcat:rvkmcmn5t5apbmnezt2k7uzc74
Self-Correction for Human Parsing
[article]
2019
arXiv
pre-print
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Labeling pixel-level masks for fine-grained semantic segmentation tasks, e.g. human parsing, remains a challenging task. ...
To tackle the problem of learning with label noises, this work introduces a purification strategy, called Self-Correction for Human Parsing (SCHP), to progressively promote the reliability of the supervised ...
Acknowledgement We thank Ting Liu and Tao Ruan for providing insights and expertise to improve this work. ...
arXiv:1910.09777v1
fatcat:oyyexar3ijbmbnmxhnoilfkope
Trans4Trans: Efficient Transformer for Transparent Object and Semantic Scene Segmentation in Real-World Navigation Assistance
[article]
2021
arXiv
pre-print
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In this paper, we build a wearable system with a novel dual-head Transformer for Transparency (Trans4Trans) perception model, which can segment general- and transparent objects. ...
Meanwhile, the Tran4Trans model has outstanding performances on driving scene datasets. ...
Our proposed approach outperforms both these aforementioned competitive networks such as OCNet and transformer-based encoder-decoder architectures such as PVT. ...
arXiv:2108.09174v1
fatcat:raco7sb4ybcerbqbpppixxn67q
AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing
[article]
2021
arXiv
pre-print
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In this paper, we propose a new model, called Attention-Augmented Network (AttaNet), to capture both global context and multilevel semantics while keeping the efficiency high. ...
Two factors have proven to be very important to the performance of semantic segmentation models: global context and multi-level semantics. ...
Acknowledgments This work is supported in part by funding from Shenzhen Institute of Artificial Intelligence and Robotics for Society, and Shenzhen NSF JCYJ20190813170601651. ...
arXiv:2103.05930v1
fatcat:icpiordlujbz3hkfhjhprp7kdy
Evaluation of Deep Learning Segmentation Models for Detection of Pine Wilt Disease in Unmanned Aerial Vehicle Images
2021
Remote Sensing
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., fully convolutional networks for semantic segmentation, DeepLabv3+, and PSPNet) were trained and evaluated. ...
Also, an atrous spatial pyramid pooling module encoded multiscale context information, and the encoder–decoder architecture recovered location/spatial information, being the best architecture for segmenting ...
Acknowledgments: We thank the Landscape and Forestry Bureau of Qindao for supporting the collection of UAV data.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs13183594
fatcat:dykrbm4xezdorpai3vngnexkmq
Dual Attention Network for Scene Segmentation
[article]
2019
arXiv
pre-print
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Unlike previous works that capture contexts by multi-scale features fusion, we propose a Dual Attention Networks (DANet) to adaptively integrate local features with their global dependencies. ...
We achieve new state-of-the-art segmentation performance on three challenging scene segmentation datasets, i.e., Cityscapes, PASCAL Context and COCO Stuff dataset. ...
The concurrent work OCNet [27] adopts self-attention mechanism with ASPP to exploit context dependencies. ...
arXiv:1809.02983v4
fatcat:6jowndquhbg3tgcuohmtuwazmu
Global-and-Local Context Network for Semantic Segmentation of Street View Images
2020
Sensors
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objects in a scene, thus reducing segmentation errors. ...
Semantic segmentation of street view images is an important step in scene understanding for autonomous vehicle systems. ...
Self-attention is also used in OCNet [23] to learn pixel-level object context information to enhance context aggregation. ...
doi:10.3390/s20102907
pmid:32455537
fatcat:tmlnyjqzivbibeqklgyot3bxdm
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