As an interdisciplinary field integrating computer vision， graphics， artificial intelligence， and optical imaging， 3D vision serves as the foundational cornerstone for building embodied general intelligence and the metaverse ecosystem. In 2024， differentiable representation technologies， exemplified by NeRF and Gaussian Splatting， continued to evolve and refine， gradually transcending the boundaries of traditional 3D reconstruction. Significant improvements in accuracy have been achieved across a spectrum from microscopic cellular structures to macroscopic physical celestial bodies， and from static scenes to dynamic human bodies. Propelled by advancements in generative artificial intelligence technologies and the scaling laws of large models， the field of 3D vision has witnessed a paradigm shift from optimization to generalizable feedforward generation， marking important progress and breakthroughs in the direction of controllable digital content generation. Embodied intelligence remains a focal point of interest， with researchers increasingly recognizing the capture and generation of 3D virtual simulation data and 3D human motion data as central to training embodied intelligence. As the concepts of world models and spatial intelligence become hot topics in the technology community， modeling the physical world， understanding spatial relationships， and predicting future states have emerged as crucial research directions， all of which rely on the support of 3D vision technologies. Furthermore， innovations in computational imaging technology have overcome the physical limitations and performance bottlenecks of traditional 3D reconstruction through non-traditional visual sensors and novel reconstruction algorithms. These technological breakthroughs are propelling 3D vision into a new era characterized by an intelligent， large-scale learning process encompassing perception， modeling， generation， and interaction. Specifically， the development trends in 3D vision primarily manifested in the following aspects：• Controllable and Physics-Aware Generation of Visual Content AIGC. With the rapid development of AI-Generated Content （AIGC） technology， visual content generation is evolving from simple 2D image creation toward more controllable and physics-aware approaches. This trend requires the introduction of multidimensional control parameters such as 3D viewpoints， lighting conditions， and 3D character motion， combined with physical prior knowledge， to achieve higher-quality content generation. 3D vision technology plays a pivotal role in this process， providing essential spatial-temporal and physical constraints for AIGC.• 4D Spatial Intelligence： Bridging Virtual and Physical Worlds. 4D spatial intelligence （3D space + time dimension） is emerging as a core technology connecting virtual worlds （e.g.， the metaverse） and physical realities （e.g.， embodied intelligent robots）. This technology focuses on establishing a digital mapping of dynamic physical environments. Leveraging 3D vision and multimodal large model technologies， AI systems can construct 4D spatial models to understand spatial relationships， predict motion trajectories， and simulate future evolutions. Concurrently， intelligent agents can interactively learn within physical or virtual 4D environments to acquire intelligence.• Data-Driven Embodied Intelligence： 3D Virtual Simulation and Human Motion Capture. The advancement of embodied intelligence heavily relies on high-quality 3D virtual simulation data and the capture/generation of human 3D motion data. These datasets serve as the "fuel" for training embodied intelligent robots to achieve sophisticated behavioral control. Through high-precision 3D vision technologies， robots can better understand and simulate human actions， thereby demonstrating enhanced intelligence in complex tasks.• Differentiable 3D Representation and Integration with Large Model Technologies. Novel 3D representations such as NeRF and 3D Gaussian Splatting are driving performance improvements in scene generation and reconstruction across scales—from microscopic cellular structures to indoor environments， human/animal modeling， autonomous driving/city modeling， and even astronomical black hole reconstruction. Their efficiency and flexibility have opened up new possibilities for 3D vision applications. Furthermore， by integrating large-scale 3D data with transformer-based architectures and advanced generative methods like diffusion models， fundamental 3D vision tasks are being unified into efficient end-to-end frameworks， achieving scaled-up learning of core 3D vision paradigms.The breakthroughs in 3D vision in 2024 have injected new momentum into technological development， with future trends focusing on several key directions. Spatiotemporal-consistent world models， integrating 4D spacetime and physical laws， will provide dynamic prediction and interaction support for complex scenarios like autonomous driving and embodied intelligence. The deep integration of generative AI and 3D content generation technologies will overcome data bottlenecks， enabling automated creation of high-fidelity and controllable 3D content. Enhanced cross-modal generalization capabilities will strengthen the fusion of vision， language， and motion modalities， improving the adaptability and robustness of robotic strategies. Physics-driven dynamic reconstruction， combined with physical engines， will achieve high-precision modeling and interactive editing of dynamic scenes， advancing digital twins and virtual reality. Meanwhile， 3D imaging technologies will accelerate scientific exploration in astrophysics and cell biology. Efficient real-time processing and lightweight solutions will boost the reconstruction and rendering efficiency of large-scale dynamic scenes， promoting edge device applications. Ethical and privacy protection will emerge as critical concerns， balancing innovation and security through encryption technologies and regulatory frameworks governing 3D data acquisition and generation. 3D vision is evolving toward an era of more intelligent and universal "spatial intelligence，" where technological breakthroughs will reshape human-computer interaction， scientific exploration， and industrial ecosystems. To foster academic exchange， this article analyzes cutting-edge trends in 3D vision and highlights the top ten research breakthroughs of the year， offering insights and references for both academia and industry.