Conceptsynthetic augmentation / 数据合成增强

Synthetic Data Augmentation

A set of techniques that expand training datasets by leveraging existing data or generative models through methods such as paraphrasing, back-translation, style transfer, and example generation. It is commonly used to alleviate data scarcity in NLP tasks.

Timeline (last 90 days)

Oct 8

Using Person Remover to obtain a person-free background image and then compositing the target character can generate paired before/after training samples for replacement.

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Using Person Remover to obtain a person-free background image and then compositing the target character can generate paired before/after training samples for replacement.

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Source Articles

MiniMax H3 Person Remover LoRA Released: Generating Better Data for Character SwapOct 8 BharatGather: A Cultural-Aware Benchmark Dataset for Misinformation Detection at Indian Public GatheringsSep 11