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ssc.io | ||
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kpzhang93.github.io
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| | | | | Face detection and alignment in unconstrained environment are challenging due to various poses, illuminations and occlusions. Recent studies show that deep learning approaches can achieve impressive performance on these two tasks. In this paper, we propose a deep cascaded multi-task framework which exploits the inherent correlation between detection and alignment to boost up their performance. In particular, our framework leverages a cascaded architecture with three stages of carefully designed deep convolutional networks to predict face and landmark location in a coarse-to-fine manner. In addition, we propose a new online hard sample mining strategy that further improves the performance in practice. Our method achieves superior accuracy over the state-of-th... | |
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bartoszmilewski.com
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| | | | | There are many excellent AI papers and tutorials that explain the attention pattern in Large Language Models. But this essentially simple pattern is often obscured by implementation details and optimizations. In this post I will try to cut to the essentials. In a nutshell, the attention machinery tries to get at a meaning of a... | |
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deepmind.google
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| | | | | We ask the question: "What is the optimal model size and number of training tokens for a given compute budget?" To answer this question, we train models of various sizes and with various numbers... | |
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blogditifet.com
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