Results 21 to 30 of about 1,221,513 (328)
Detail Guided Multilateral Segmentation Network for Real-Time Semantic Segmentation
Applied Sciences, 2022 With the development of unmanned vehicles and other technologies, the technical demand for scene semantic segmentation is more and more intense.
Qunyan Jiang +6 more
doaj +1 more source
Delivering Arbitrary-Modal Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2023 Multimodal fusion can make semantic segmentation more robust. However, fusing an arbitrary number of modalities remains underexplored. To delve into this problem, we create the Deliver arbitrary-modal segmentation benchmark, covering Depth, LiDAR ...
Jiaming Zhang +8 more
semanticscholar +1 more source
Frontiers in Earth Science, 2023 In the era of artificial intelligence and big data, semantic segmentation of images plays a vital role in various fields, such as people’s livelihoods and the military.
Guoxun Zheng +8 more
doaj +1 more source
A TWO-STAGE APPROACH FOR RARE CLASS SEGMENTATION IN LARGE-SCALE URBAN POINT CLOUDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Although deep learning has greatly improved the semantic segmentation accuracy of point clouds, the segmentation of rare classes in large-scale urban scenes has not been targeted in available methods.
X. Zhang, R. Xue, R. Xue, U. Soergel
doaj +1 more source
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2021 As acquiring pixel-wise annotations of real-world images for semantic segmentation is a costly process, a model can instead be trained with more accessible synthetic data and adapted to real images without requiring their annotations.
Lukas Hoyer, Dengxin Dai, L. Gool
semanticscholar +1 more source
CAT-Seg: Cost Aggregation for Open-Vocabulary Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2023 Open-vocabulary semantic segmentation presents the challenge of labeling each pixel within an image based on a wide range of text descriptions. In this work, we introduce a novel cost-based approach to adapt vision-language foundation models, notably ...
Seokju Cho +7 more
semanticscholar +1 more source
Enhancing Semantically Masked Transformer With Local Attention for Semantic Segmentation
IEEE Access, 2023 Transformer-based semantic segmentation has been applied to various visual recognition applications and achieved outstanding performance in recent years. Since most of these approaches adopt a pretrained backbone and finetune it for semantic segmentation,
Zhengyu Xia, Joohee Kim
doaj +1 more source
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation [PDF]
European Conference on Computer Vision, 2018 Semantic segmentation requires both rich spatial information and sizeable receptive field. However, modern approaches usually compromise spatial resolution to achieve real-time inference speed, which leads to poor performance.
Changqian Yu +5 more
semanticscholar +1 more source
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation [PDF]
Computer Vision and Pattern Recognition, 2022 In this work, we revisit the weak-to-strong consistency framework, popularized by FixMatch from semi-supervised classification, where the prediction of a weakly perturbed image serves as supervision for its strongly perturbed version.
Lihe Yang +4 more
semanticscholar +1 more source
Sensors, 2022 Semantic segmentation network-based methods can detect concrete damage at the pixel level. However, the performance of a single semantic segmentation network is often limited.
Shengyuan Li, Xuefeng Zhao
doaj +1 more source