Open Source AI Project


NeMo is a project that introduces 3D Neural Motion Fields for generating 3D motion from multiple video instances of the same action.


NeMo stands as a pioneering project in the realm of computer vision, particularly within the context of 3D motion capture and synthesis. Developed for presentation at the esteemed Computer Vision and Pattern Recognition (CVPR) conference in 2023, NeMo introduces the concept of 3D Neural Motion Fields. This innovative approach is aimed at generating three-dimensional motion from several video instances that capture the same action. By leveraging multiple videos of the same action, NeMo seeks to deeply understand and synthesize 3D actions, facilitating the creation of detailed and dynamic 3D reconstructions of complex movements.

The significance of NeMo’s approach lies in its ability to process and interpret the intricate dynamics of actions as captured in video format, transcending traditional limitations associated with 3D motion capture. Instead of relying on single video feeds or requiring specialized hardware, NeMo utilizes the depth of information available across multiple video instances. This method allows for a richer, more nuanced understanding of movement, capturing subtleties and variations that occur naturally within the execution of any action.

By synthesizing 3D actions from videos, NeMo opens up new possibilities for applications in fields such as virtual reality (VR), augmented reality (AR), film production, and game development. It enables creators to produce lifelike animations and simulations with a level of detail and realism previously difficult to achieve. Moreover, NeMo’s technology could significantly impact the development of educational tools, sports analysis software, and medical rehabilitation programs by providing accurate 3D representations of human movement.

The project’s presentation at CVPR 2023 highlights its contribution to the ongoing advancements in computer vision technology. By focusing on understanding and synthesizing 3D actions from videos, NeMo addresses a crucial challenge in the field—creating dynamic and detailed 3D reconstructions of complex movements. This not only pushes the boundaries of what’s possible in motion analysis and generation but also paves the way for future innovations in how we capture, interpret, and recreate the physical world in digital form.

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