Current multi-view gaze estimation remains limited by existing datasets, insufficient exploitation of complementary cross-view information, and evaluation focused primarily on average gaze error. We address these limitations through a more systematic study of multi-view gaze estimation. First, we introduce PrismGaze, a...
Chang Liu, Jia-Qi Liu, Cheng-Wen Zhang et al.· 1 citation
The architectural improvements and novel training recipe allow PaGE to achieve state-of-the-art performance on several gaze estimation tasks, outperforming humans in 7 out of 9 metrics while reducing the human-AI gap by at least 60% in the remaining 2.
Zhou-Tong Ye, Cheng-Wen Zhang, Zhai-Bin Cui et al.· arXiv.org· 0 citations
U-Lens improves verification efficiency and effort allocation, reduced perceived workload, and strengthened support across all three stages of uncertainty management, and reframes uncertainty support for generative AI from text-centered cues to a user-centered process of interpreting, evaluating, and acting on uncertai...
Yu Mei, Qingyue Zhuang, Jie Cai et al.· arXiv.org· 0 citations
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