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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Mark Lee, Zico Kolter |
| 2019 |
| arxiv 1906.11897 |
| Multi-Channel CNN-based Object Detection for Enhanced Situation Awareness | Shuo Liu, Zheng Liu | 2017 | arxiv 1712.00075 |
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| DEYO: DETR with YOLO for Step-by-Step Object Detection | Haodong Ouyang | 2022 | arxiv 2211.06588 |
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| LLM-Guided Agentic Object Detection for Open-World Understanding | Furkan Mumcu, Michael J. Jones, Anoop Cherian | 2025 | arxiv 2507.10844 |
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| WW-Nets: Dual Neural Networks for Object Detection | Mohammad K. Ebrahimpour, J. Ben Falandays, Samuel Spevack | 2020 | arxiv 2005.07787 |
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| SPWOOD: Sparse Partial Weakly-Supervised Oriented Object Detection | Wei Zhang, Xiang Liu, Ningjing Liu | 2026 | arxiv 2602.03634 |
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| Model-agnostic explainable artificial intelligence for object detection in image data | Milad Moradi, Ke Yan, David Colwell | 2023 | arxiv 2303.17249 |
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| Cross-Modality 3D Object Detection | Ming Zhu, Chao Ma, Pan Ji | 2020 | arxiv 2008.10436 |
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| Rotationally Equivariant 3D Object Detection | Hong-Xing Yu, Jiajun Wu, Li Yi | 2022 | arxiv 2204.13630 |
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| Towards Stable 3D Object Detection | Jiabao Wang, Qiang Meng, Guochao Liu | 2024 | arxiv 2407.04305 |
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