We introduce Stanford-ORB, a new real-world 3D Object inverse Rendering Benchmark.
Recent advances in inverse rendering have enabled a wide range of real-world applications …

We study recovering fluid density and velocity from sparse multiview videos. Existing neural
dynamic reconstruction methods predominantly rely on optical flows; therefore, they cannot …

The covariance matrix adaptation evolution strategy (CMA-ES) is one of the most successful
methods for solving continuous black-box optimization problems. A practically useful aspect …

Monocular 3D reconstruction for categorical objects heavily relies on accurately perceiving
each object's pose. While gradient-based optimization within a NeRF framework updates …

Current AI systems still fail to match the flexibility, robustness, and generalizability of human
intelligence: how even a young child can manipulate objects to achieve goals of their own …

Monocular 3D reconstruction for categorical objects heavily relies on accurately perceiving
each object's pose. While gradient-based optimization in a NeRF framework updates the …

Neural radiance fields (NeRFs) are a powerful tool for implicit scene representations,
allowing for differentiable rendering and the ability to make predictions about previously …