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arXiv Computer Vision research summaries for April 30, 2024.
Today's Research Themes (AI-Generated):
• Transition Rate Scheduling enhances Quantization-Aware Training by explicitly controlling the number of transitions of quantized weights.
• The proposed debiasing method uses spatial guidance to steer models towards learning intrinsic features, improving bias-aligned sample performance.
• DELINE8K dataset, incorporating diverse document elements, shows superior performance in semantic segmentation of historical documents.
• A novel application of Pix2Pix GANs offers accurate ground truth image creation for urban planning and autonomous vehicle training.
• Vision transformer networks enhance drone-to-drone detection with a novel coarse-to-fine detection strategy, delivering real-time capabilities.
arXiv Computer Vision research summaries for April 30, 2024.
Today's Research Themes (AI-Generated):
• Transition Rate Scheduling enhances Quantization-Aware Training by explicitly controlling the number of transitions of quantized weights.
• The proposed debiasing method uses spatial guidance to steer models towards learning intrinsic features, improving bias-aligned sample performance.
• DELINE8K dataset, incorporating diverse document elements, shows superior performance in semantic segmentation of historical documents.
• A novel application of Pix2Pix GANs offers accurate ground truth image creation for urban planning and autonomous vehicle training.
• Vision transformer networks enhance drone-to-drone detection with a novel coarse-to-fine detection strategy, delivering real-time capabilities.