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Found 3 papers, 2 papers with code
Virtual Classification: Modulating Domain-Specific Knowledge for Multidomain Crowd Counting
Multidomain crowd counting aims to learn a general model for multiple diverse datasets.
Regressor-Segmenter Mutual Prompt Learning for Crowd Counting
In this study, we propose mutual prompt learning (mPrompt), which leverages a regressor and a segmenter as guidance for each other, solving bias and inaccuracy caused by annotation variance while distinguishing foreground from background.
PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation
To enhance the generalization ability of PanGu-$\alpha$, we collect 1. 1TB high-quality Chinese data from a wide range of domains to pretrain the model.
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