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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| arxiv 1811.00539 |
| Composite Binary Decomposition Networks | You Qiaoben, Zheng Wang, Jianguo Li | 2018 | arxiv 1811.06668 |
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| SurfConv: Bridging 3D and 2D Convolution for RGBD Images | Hang Chu, Wei-Chiu Ma, Kaustav Kundu | 2018 | arxiv 1812.01519 |
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| Future Segmentation Using 3D Structure | Suhani Vora, Reza Mahjourian, Soeren Pirk | 2018 | arxiv 1811.11358 |
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| Unsupervised domain adaptation for medical imaging segmentation with self-ensembling | Christian S. Perone, Pedro Ballester, Rodrigo C. Barros | 2018 | arxiv 1811.06042 |
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| Real-Time Freespace Segmentation on Autonomous Robots for Detection of Obstacles and Drop-Offs | Anish Singhani | 2019 | arxiv 1902.00842 |
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| Large-Scale Visual Active Learning with Deep Probabilistic Ensembles | Kashyap Chitta, Jose M. Alvarez, Adam Lesnikowski | 2018 | arxiv 1811.03575 |
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| Adversarial Pixel-Level Generation of Semantic Images | Emanuele Ghelfi, Paolo Galeone, Michele De Simoni | 2019 | arxiv 1906.12195 |
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| Object Segmentation using Pixel-wise Adversarial Loss | Ricard Durall, Franz-Josef Pfreundt, Ullrich Köthe | 2019 | arxiv 1909.10341 |
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| Learning Across Tasks and Domains | Pierluigi Zama Ramirez, Alessio Tonioni, Samuele Salti | 2019 | arxiv 1904.04744 |
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| Sampling-free Epistemic Uncertainty Estimation Using Approximated Variance Propagation | Janis Postels, Francesco Ferroni, Huseyin Coskun | 2019 | arxiv 1908.00598 |
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