The incorporation of physical information in machine learning frameworks is opening and
transforming many application domains. Here the learning process is augmented through …

We introduce PhysGaussian a new method that seamlessly integrates physically grounded
Newtonian dynamics within 3D Gaussians to achieve high-quality novel motion synthesis …

The proliferation of technologies, such as extended reality (XR), has increased the demand
for high-quality three-dimensional (3D) graphical representations. Industrial 3D applications …

Realistic object interactions are crucial for creating immersive virtual experiences, yet
synthesizing realistic 3D object dynamics in response to novel interactions remains a …

As 3D content becomes increasingly prevalent, there'sa growing focus on the development
of engagements with 3D virtual content. Unfortunately, traditional techniques for creating …

We present PhysGen, a novel image-to-video generation method that converts a single
image and an input condition (eg., force and torque applied to an object in the image) to …

Embedding polygonal mesh assets within photorealistic Neural Radience Fields (NeRF)
volumes, such that they can be rendered and their dynamics simulated in a physically …

Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Reconstructing and simulating elastic objects from visual observations is crucial for
applications in computer vision and robotics. Existing methods, such as 3D Gaussians …

We show that physics-based simulations can be seamlessly integrated with NeRF to
generate high-quality elastodynamics of real-world objects. Unlike existing methods we …