4 citations · 5 across the 3 of their papers we have counts for
5 papers
Neural Implicit Event Generator for Motion Tracking
Mana Masuda, Yusuke Sekikawa, Ryo Fujii +1
We present a novel framework of motion tracking from event data using implicit expression. Our framework use pre-trained event generation MLP named implicit event generator (IEG) a…
Irregularly Tabulated MLP for Fast Point Feature Embedding
Yusuke Sekikawa, Teppei Suzuki
Aiming at drastic speedup for point-feature embeddings at test time, we propose a new framework that uses a pair of multi-layer perceptrons (MLP) and a lookup table (LUT) to transf…
Rethinking PointNet Embedding for Faster and Compact Model
Teppei Suzuki, Keisuke Ozawa, Yusuke Sekikawa
PointNet, which is the widely used point-wise embedding method and known as a universal approximator for continuous set functions, can process one million points per second. Nevert…
Tabulated MLP for Fast Point Feature Embedding
Yusuke Sekikawa, Teppei Suzuki
Aiming at a drastic speedup for point-data embeddings at test time, we propose a new framework that uses a pair of multi-layer perceptron (MLP) and look-up table (LUT) to transform…
EventNet: Asynchronous Recursive Event Processing
Yusuke Sekikawa, Kosuke Hara, Hideo Saito
Event cameras are bio-inspired vision sensors that mimic retinas to asynchronously report per-pixel intensity changes rather than outputting an actual intensity image at regular in…