4 citations · 13 across the 8 of their papers we have counts for
8 papers
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…
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…
Implicit Neural Representations for Variable Length Human Motion Generation
Pablo Cervantes, Yusuke Sekikawa, Ikuro Sato +1
We propose an action-conditional human motion generation method using variational implicit neural representations (INR). The variational formalism enables action-conditional distri…
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…