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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Dynamic Multi-Scale Loss Optimization for Object Detection | Yihao Luo, Xiang Cao, Juntao Zhang | 2021 | arxiv 2108.04014 |
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| Selective Probabilistic Classifier Based on Hypothesis Testing | Saeed Bakhshi Germi, Esa Rahtu, Heikki Huttunen | 2021 | arxiv 2105.03876 |
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| How Does Heterogeneous Label Noise Impact Generalization in Neural Nets? | Bidur Khanal, Christopher Kanan | 2021 | arxiv 2106.15475 |
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| Unifying Multimodal Transformer for Bi-directional Image and Text Generation | Yupan Huang, Hongwei Xue, Bei Liu | 2021 | arxiv 2110.09753 |
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| Repaint: Improving the Generalization of Down-Stream Visual Tasks by Generating Multiple Instances of Training Examples | Amin Banitalebi-Dehkordi, Yong Zhang | 2021 | arxiv 2110.10366 |
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| Beyond Classification: Knowledge Distillation using Multi-Object Impressions | Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri | 2021 | arxiv 2110.14215 |
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| Aligning Pretraining for Detection via Object-Level Contrastive Learning | Fangyun Wei, Yue Gao, Zhirong Wu | 2021 | arxiv 2106.02637 |
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| Meta-Learning for Multi-Label Few-Shot Classification | Christian Simon, Piotr Koniusz, Mehrtash Harandi | 2021 | arxiv 2110.13494 |
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| UFO: A UniFied TransfOrmer for Vision-Language Representation Learning | Jianfeng Wang, Xiaowei Hu, Zhe Gan | 2021 | arxiv 2111.10023 |
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| Benchmarking Detection Transfer Learning with Vision Transformers | Yanghao Li, Saining Xie, Xinlei Chen | 2021 | arxiv 2111.11429 |
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