Deep Event Visual Odometry

Deep Event Visual Odometry

Deep Event Visual Odometry sparsely tracks selected event patches over time. A key component of DEVO is a novel deep patch selection mechanism tailored to event data. We significantly decrease the pose tracking error on seven real-world benchmarks by up to 97% compared to event-only methods and often surpass or are close to stereo or inertial methods.

Prophesee Introduces Metavision SDK5 Pro

Prophesee Introduces Metavision SDK5 Pro

With Metavision SDK5 PRO, evaluate, design and sell your own Metavision product. Now included at no additional cost in both binaries and source form with every Prophesee USB EVK purchase.

Neuromorphic Wireless Device-Edge Co-Inference via the Directed Information Bottleneck

Neuromorphic Wireless Device-Edge Co-Inference via the Directed Information Bottleneck

The proposed system is designed using a transmitter-centric information-theoretic criterion that targets a reduction of the communication overhead, while retaining the most relevant information for the end-to-end semantic task of interest. Numerical results on standard data sets validate the proposed architecture, and a preliminary testbed realization is reported.