Each photo in an image burst can be considered a sample of a complex 3D scene: the
product of parallax diffuse and specular materials scene motion and illuminant variation …

Neural radiance fields (NeRFs) have become a ubiquitous tool for modeling scene
appearance and geometry from multiview imagery. Recent work has also begun to explore …

We investigate the generalization capabilities of neural signed distance functions (SDFs) for
learning 3D object representations for unseen and unlabeled point clouds. Existing methods …

Underwater perception and 3D surface reconstruction are challenging problems with broad
applications in construction, security, marine archaeology, and environmental monitoring …

We propose a method for adapting neural networks to distribution shifts at test-time. In
contrast to training-time robustness mechanisms that attempt to anticipate the shift, we …

We present an image formation model and optimization procedure that combines the
advantages of neural radiance fields and structured light imaging. Existing depth-supervised …

We show how to turn a noisy and fragile active triangulation technique--three-pattern
structured light with a grayscale camera--into a fast and powerful tool for 3D capture: able to …

Modern mobile burst photography pipelines capture and merge a short sequence of frames
to recover an enhanced image, but often disregard the 3D nature of the scene they capture …

The perception of 3D motion of surrounding traffic participants is crucial for driving safety.
While existing works primarily focus on general large motions we contend that the …

Direct time-of-flight (dToF) sensors are promising for next-generation on-device 3D sensing.
However, limited by manufacturing capabilities in a compact module, the dToF data has low …