What is the true heart of mental healthcare -- innovation or humanity? Can
virtual therapy ever replicate the profound human bonds where healing arises?
As artificial intelligence and immersive technologies promise expanded access,
safeguards must ensure technologies remain supplementary tools guided by
providers' wisdom. Implementation requires nuance balancing efficiency and
empathy. If conscious of ethical risks, perhaps AI could restore humanity by
automating tasks, giving providers more time to listen. Yet no algorithm can
replicate the seat of dignity within. We must ask ourselves: What future has
people at its core? One where AI thoughtfully plays a collaborative role? Or
where pursuit of progress leaves vulnerability behind? This commentary argues
for a balanced approach thoughtfully integrating technology while retaining
care's irreplaceable human essence, at the heart of this profoundly human
profession. Ultimately, by nurturing innovation and humanity together, perhaps
we reach new heights of empathy previously unimaginable.

在心理保健中，创新和人文关怀哪一个是真正的核心？虚拟疗法能否复制出治愈起源于人际关系的深厚纽带？人工智能和沉浸式技术承诺扩大获取的机会，但必须确保技术仍然是提供者智慧指导下的辅助工具。实施需要在效率和同理心之间保持微妙的平衡。如果能意识到道德风险，也许人工智能可以通过自动化任务为提供者节省更多时间来倾听，从而恢复人文关怀。然而，没有算法能够复制尊严的根本。我们必须问自己：未来是以人为核心的未来吗？还是追求进步抛下了脆弱之处？本评论认为，应该在综合技术的同时保留护理不可替代的人文精髓，这是这个极其人性化的职业的核心。最终，通过共同培养创新和人文关怀的结合，也许我们可以达到以前难以想象的同理心新高度。

机器无法取代人的心脏

The Machine Can't Replace the Human Heart

The volumetric representation of human interactions is one of the fundamental
domains in the development of immersive media productions and telecommunication
applications. Particularly in the context of the rapid advancement of Extended
Reality (XR) applications, this volumetric data has proven to be an essential
technology for future XR elaboration. In this work, we present a new multimodal
database to help advance the development of immersive technologies. Our
proposed database provides ethically compliant and diverse volumetric data, in
particular 27 participants displaying posed facial expressions and subtle body
movements while speaking, plus 11 participants wearing head-mounted displays
(HMDs). The recording system consists of a volumetric capture (VoCap) studio,
including 31 synchronized modules with 62 RGB cameras and 31 depth cameras. In
addition to textured meshes, point clouds, and multi-view RGB-D data, we use
one Lytro Illum camera for providing light field (LF) data simultaneously.
Finally, we also provide an evaluation of our dataset employment with regard to
the tasks of facial expression classification, HMDs removal, and point cloud
reconstruction. The dataset can be helpful in the evaluation and performance
testing of various XR algorithms, including but not limited to facial
expression recognition and reconstruction, facial reenactment, and volumetric
video. HEADSET and its all associated raw data and license agreement will be
publicly available for research purposes.

我们提出了一个新的多模态数据库来帮助推进沉浸技术的发展，该数据库提供了符合道德规范并且多样化的体积数据，可以支持面部表情识别等扩展现实算法的评估和性能测试。

头戴式耳机：部分遮挡的多模感知人类情感数据集

Headset: Human emotion awareness under partial occlusions multimodal  dataset

The imminent impact of immersive technologies in society urges for active
research in real-time and interactive physics simulation for virtual worlds to
be realistic. In this context, realistic means to be compliant to the laws of
physics. In this paper we present a method for computing the dynamic response
of (possibly non-linear and dissipative) deformable objects induced by
real-time user interactions in mixed reality using deep learning. The
graph-based architecture of the method ensures the thermodynamic consistency of
the predictions, whereas the visualization pipeline allows a natural and
realistic user experience. Two examples of virtual solids interacting with
virtual or physical solids in mixed reality scenarios are provided to prove the
performance of the method.

本文介绍了一种基于深度学习的方法，用于计算混合现实中用户实时交互引起的（可能是非线性和耗散性的）可变形物体的动态响应，以保证虚拟世界的正确性和真实性。两个具体示例证明了该方法的高效性。