WebDec 1, 2024 · DOI: 10.1016/j.isprsjprs.2024.09.019 Corpus ID: 225168491; Parsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss @article{Zheng2024ParsingVH, title={Parsing very high resolution urban scene images by learning deep ConvNets with edge-aware loss}, author={Xianwei Zheng and Linxi … WebMar 5, 2024 · For the second issue, we design an edge-aware loss which is effective in distinguishing the boundaries of object/stuff. With these two designs, our Multi Receptive Field Network achieves new state-of-the-art results on two widely-used semantic segmentation benchmark datasets. Specifically, we achieve a mean IoU of 83.0% on the …
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WebFeb 16, 2024 · In summary, our main contributions are: (1) Three new loss functions that use a greyscale saliency mask for edge-aware bokeh rendering from monocular images taken with wide depth-of-field. (2) A multi-stage training scheme that adversarially refines the output produced using the three aforementioned losses. (3) WebMay 26, 2024 · Edge awareness loss, which based on edge obtained by traditional Laplacian method instead of image, is proposed to strengthen the robustness of different lighting conditions. In addition, the computational cost of Laplacian edge is lower than that obtained by neural network. 2 Proposed method phormisios
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WebZheng et al. [28] developed a Dice-based edge-aware loss function to refine edge information directly from semantic segmentation prediction. ... Semantic Segmentation of High-Resolution Remote... WebMar 5, 2024 · To effectively incorporate edge cues, we propose the edge-aware smoothness loss and edge feature embedding for inter-task interactions. It is demonstrated that based on our unified model, edge detection … WebDec 1, 2024 · To effectively separate confusing objects with sharp contours, a Dice-based edge-aware loss function (EA loss) is devised to guide the EaNet to refine both the … phormium and dogs