activity
20182023
most citedTabulated MLP for Fast Point Feature Embedding

4 citations · 6 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CV2023

Event-based Camera Tracker by t NeRF

Mana Masuda, Yusuke Sekikawa, Hideo Saito

When a camera travels across a 3D world, only a fraction of pixel value changes; an event-based camera observes the change as sparse events. How can we utilize sparse events for ef…

cs.CV20231 cited

Toward Unsupervised 3D Point Cloud Anomaly Detection using Variational Autoencoder

Mana Masuda, Ryo Hachiuma, Ryo Fujii +2

In this paper, we present an end-to-end unsupervised anomaly detection framework for 3D point clouds. To the best of our knowledge, this is the first work to tackle the anomaly det…

cs.CV2021

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…

cs.CV2020

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…

cs.CV20194 cited

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…

cs.CV2018

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…