SOTA2 Research · papers

Papers for “semantic segmentation”

Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.

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20 indexed

Title	Authors	Year	Source
Differentially private federated deep learning for multi-site medical image segmentation	Alexander Ziller, Dmitrii Usynin, Nicolas Remerscheid	2021	arxiv 2107.02586
Level generation and style enhancement -- deep learning for game development overview	Piotr Migda\l, Bart\lomiej Olechno, B\la\.zej Podgórski	2021	arxiv 2107.07397
Puzzle-CAM: Improved localization via matching partial and full features	Sanghyun Jo, In-Jae Yu	2021	arxiv 2101.11253
Disentangled Latent Transformer for Interpretable Monocular Height Estimation	Zhitong Xiong, Sining Chen, Yilei Shi	2022	arxiv 2201.06357
MultiTask-CenterNet (MCN): Efficient and Diverse Multitask Learning using an Anchor Free Approach	Falk Heuer, Sven Mantowsky, Syed Saqib Bukhari	2021	arxiv 2108.05060
Centroid-UNet: Detecting Centroids in Aerial Images	N. Lakmal Deshapriya, Dan Tran, Sriram Reddy	2021	arxiv 2112.06530
Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks	Yiyi Liao, Sarath Kodagoda, Yue Wang	2015	arxiv 1509.06470
MortonNet: Self-Supervised Learning of Local Features in 3D Point Clouds	Ali Thabet, Humam Alwassel, Bernard Ghanem	2019	arxiv 1904.00230
Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation	Xuhua Ren, Lichi Zhang, Sahar Ahmad	2019	arxiv 1905.08720
Cell segmentation from telecentric bright-field transmitted light microscopy images using a Residual Attention U-Net: a case study on HeLa line