Transient imaging has recently made a huge impact in the computer graphics and computer
vision fields. By capturing, reconstructing, or simulating light transport at extreme temporal …

Traditional color images only depict color intensities in red, green and blue channels, often
making object trackers fail in challenging scenarios, eg, background clutter and rapid …

Computer vision algorithms build on 2D images or 3D videos that capture dynamic events at
the millisecond time scale. However, capturing and analyzing" transient images" at the …

Time-correlated imaging is an emerging sensing modality that has been shown to enable
promising application scenarios, including lidar ranging, fluorescence lifetime imaging, and …

Laser cutter users face difficulties distinguishing between visually similar materials. This can
lead to problems, such as using the wrong power/speed settings or accidentally cutting …

Depth sensors have emerged as a cornerstone sensor modality with diverse applications in
personal hand-held devices, robotics, scientific imaging, autonomous vehicles, and more. In …

Ground surfaces are often carefully designed and engineered with various textures to fit the
functionalities of human environments and thus could contain rich context information for …

Material recognition can help inform robots about how to properly interact with and
manipulate real-world objects. In this paper, we present a multimodal sensing technique …

This paper introduces RFVibe, a system that enables contactless material and object
identification through the fusion of millimeter wave wireless signals with acoustic signals. In …

Indirect Time-of-Flight (iToF) cameras are a promising depth sensing technology. However,
they are prone to errors caused by multi-path interference (MPI) and low signal-to-noise ratio …