they can only perceive portion, along one or two axes, of a stimulus which is normally full of 3D space surrounding the sensors. [10,11] Another limitation is the deficient interface between the 2D sensors and target objects. For instance, health monitoring could be realized by attaching or implanting biomedical sensors to target organs or tissues of the human body. [12] However, it is difficult for traditional 2D sensors to collect accurate vital signals because they cannot conform to the 3D structure of organs or tissues. [13,14] Although this problem can be partially relieved by using flexible 2D sensors, [15] passive adaptation to target objects inevitably results in gaps. [16] Sensors with 3D structures have been developed to overcome these limitations. A 3D cubic sensor generated by selffolding has the ability to gain concentration as well as spatial information (i.e., direction and orientation) of target analytes surrounding the device. [17][18][19] Moreover, a 3D strain sensor fabricated by in situ 3D printing was observed to be compliant with the surface of a breathing porcine lung for continuous mapping of respiration-induced deformation with high 3D spatial resolution. [20] Besides full-space sensing and conformity to targets, compared to 2D counterparts, 3D sensors also possess advantages such as high sensitivity, [21] large specific surface area, [22] multimodal sensing, [23] and so forth.Despite their superiority to 2D sensors, it is challenging to fabricate a sensor with a delicate 3D configuration on a small scale because current micro-nano fabrication technologies are typically performed on planar silicon wafers. [35] Considerable efforts have been made to develop new fabrication methods for 3D sensors, which will be reviewed in this paper. According to the criterion of material quantity change, [36] these fabrication methods are divided into four categories: bulk chemical etching (subtractive manufacturing), 3D printing (additive manufacturing), molding (formative manufacturing), and stress-induced assembly (formative manufacturing), as shown in Figure 1. Basic applications or sensing functions (e.g., light, force, electricity, and chemical/gas), advanced applications (e.g., robotics, HMI, health monitoring, and tissue engineering), and strengths over 2D counterparts (high spatial resolution, multimodality, conformity, and high sensitivity) are illustrated for relevant 3D sensors. The fabrication methods and their pros and cons in generating 3D structures for various applications are summarized in Table 1. The discussions are concluded by outlining current challenges and future opportunities for 3D sensors.The intelligence of modern technologies relies on perceptual systems based on microscale sensors. However, because of the traditional top-down fabrication approaches performed on planar silicon wafers, a large proportion of existing microscale sensors have 2D structures, which severely restricts their sensing capabilities. To overcome these restrictions, over the past few decades, increasing e...