Eye contact is a crucial non-verbal interaction modality and plays an important role in our everyday social life. While humans are very sensitive to eye contact, the capabilities of machines to capture a person's gaze are still mediocre. We tackle this challenge and present NITEC, a hand-annotated eye contact dataset for ego-vision interaction. NITEC exceeds existing datasets for ego-vision eye contact in size and variety of demographics, social contexts, and lighting conditions, making it a valuable resource for advancing ego-vision-based eye contact research. Our extensive evaluations on NITEC demonstrate strong cross-dataset performance, emphasizing its effectiveness and adaptability in various scenarios, that allows seamless utilization to the fields of computer vision, human-computer interaction, and social robotics. We make our NITEC dataset publicly available to foster reproducibility and further exploration in the field of ego-vision interaction. https://github.com/thohemp/nitec

翻译：眼神接触是一种关键的非语言交互方式，在我们的日常社交生活中扮演重要角色。尽管人类对眼神接触极为敏感，但机器捕捉他人注视方向的能力仍显平庸。为应对这一挑战，我们提出NITEC——一个面向自我视觉交互的手工标注眼神接触数据集。与现有自我视觉眼神接触数据集相比，NITEC在规模、人口统计学多样性、社交情境及光照条件方面均实现了突破，成为推动基于自我视觉的眼神接触研究的重要资源。在NITEC上的广泛评估表明，该数据集拥有强大的跨数据集性能，充分凸显其在多种场景下的有效性与适应性，可无缝应用于计算机视觉、人机交互及社交机器人领域。我们已将NITEC数据集公开，以促进自我视觉交互领域的可重复研究与深入探索。https://github.com/thohemp/nitec