Results 11 to 20 of about 57,569 (167)
Semantic segmentation by semantic proportions
CoRR, 2023 Semantic segmentation is a critical task in computer vision aiming to identify and classify individual pixels in an image, with numerous applications in for example autonomous driving and medical image analysis.
Aysel, Halil Ibrahim +2 more
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Boosting Semantic Segmentation with Semantic Boundaries
CoRR, 2023 In this paper, we present the Semantic Boundary Conditioned Backbone (SBCB) framework, a simple yet effective training framework that is model-agnostic and boosts segmentation performance, especially around the boundaries.
Aoki, Yoshimitsu, Ishikawa, Haruya
core +2 more sources
Segmenter: Transformer for Semantic Segmentation [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Image segmentation is often ambiguous at the level of individual image patches and requires contextual information to reach label consensus. In this paper we introduce Segmenter, a transformer model for semantic segmentation. In contrast to convolution-based methods, our approach allows to model global context already at the first layer and throughout ...
Strudel, Robin +3 more
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Progressive Semantic Segmentation [PDF]
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 Accepted to CVPR ...
Chuong Huynh +3 more
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Domain Adaptive Semantic Segmentation without Source Data [PDF]
, 2021 Domain adaptive semantic segmentation is recognized as a promising technique to alleviate the domain shift between the labeled source domain and the unlabeled target domain in many real-world applications, such as automatic pilot.
Chen, Zhi +9 more
core +1 more source
Introspective semantic segmentation [PDF]
IEEE Winter Conference on Applications of Computer Vision, 2014 Traditional approaches for semantic segmentation work in a supervised setting assuming a fixed number of semantic categories and require sufficiently large training sets. The performance of various approaches is often reported in terms of average per pixel class accuracy and global accuracy of the final labeling. When applying the learned models in the
Gautam Singh, Jana Kosecka
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Generative Semantic Segmentation
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 To appear at CVPR2023, code at http://github.com/fudan-zvg ...
Jiaqi Chen +3 more
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3D CATBraTS: Channel Attention Transformer for Brain Tumour Semantic Segmentation [PDF]
, 2023 Brain tumour diagnosis is a challenging task yet crucial for planning treatments to stop or slow the growth of a tumour. In the last decade, there has been a dramatic increase in the use of convolutional neural networks (CNN) for their high performance ...
Bonmati Coll, E. +3 more
core +1 more source
Semantic Diffusion Network for Semantic Segmentation
Advances in Neural Information Processing Systems 35, 2022 Precise and accurate predictions over boundary areas are essential for semantic segmentation. However, the commonly-used convolutional operators tend to smooth and blur local detail cues, making it difficult for deep models to generate accurate boundary predictions.
Haoru Tan, Sitong Wu, Jimin Pi
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Semantic Amodal Segmentation [PDF]
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 major update including new COCO data, metrics, and ...
Yan Zhu 0009 +3 more
openaire +2 more sources