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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| 2025 |
| arxiv 2503.04688 |
| Approximate Size Targets Are Sufficient for Accurate Semantic Segmentation | Xingye Fan, Zhongwen (Rex) Zhang, Yuri Boykov | 2025 | arxiv 2503.06954 |
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| Comprehensive Attention Self-Distillation for Weakly-Supervised Object Detection | Zeyi Huang, Yang Zou, Vijayakumar Bhagavatula | 2020 | arxiv 2010.12023 |
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| Visual Transformers: Token-based Image Representation and Processing for Computer Vision | Bichen Wu, Chenfeng Xu, Xiaoliang Dai | 2020 | arxiv 2006.03677 |
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| Single-shot Path Integrated Panoptic Segmentation | Sukjun Hwang, Seoung Wug Oh, Seon Joo Kim | 2020 | arxiv 2012.01632 |
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| SID: Incremental Learning for Anchor-Free Object Detection via Selective and Inter-Related Distillation | Can Peng, Kun Zhao, Sam Maksoud | 2020 | arxiv 2012.15439 |
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| Augmenting Proposals by the Detector Itself | Xiaopei Wan, Zhenhua Guo, Chao He | 2021 | arxiv 2101.11789 |
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| Panoptic Lintention Network: Towards Efficient Navigational Perception for the Visually Impaired | Wei Mao, Jiaming Zhang, Kailun Yang | 2021 | arxiv 2103.04128 |
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| Dynamic Scale Training for Object Detection | Yukang Chen, Peizhen Zhang, Zeming Li | 2020 | arxiv 2004.12432 |
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| Control Distance IoU and Control Distance IoU Loss Function for Better Bounding Box Regression | Dong Chen, Duoqian Miao | 2021 | arxiv 2103.11696 |
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| BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation | Jungbeom Lee, Jihun Yi, Chaehun Shin | 2021 | arxiv 2103.08907 |
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