activity
20042022
most citedReinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition

21 citations · 80 across the 12 of their papers we have counts for

collaborators

15 papers

cs.CV20224 cited

Novel View Synthesis for High-fidelity Headshot Scenes

Satoshi Tsutsui, Weijia Mao, Sijing Lin +3

Rendering scenes with a high-quality human face from arbitrary viewpoints is a practical and useful technique for many real-world applications. Recently, Neural Radiance Fields (Ne…

physics.comp-ph2022

Bayesian Inference on Hamiltonian Selections for Mössbauer Spectroscopy

Ryota Moriguchi, Satoshi Tsutsui, Shun Katakami +3

Mössbauer spectroscopy, which provides knowledge related to electronic states in materials, has been applied to various fields such as condensed matter physics and material science…

cs.CV202221 cited

Reinforcing Generated Images via Meta-learning for One-Shot Fine-Grained Visual Recognition

Satoshi Tsutsui, Yanwei Fu, David Crandall

One-shot fine-grained visual recognition often suffers from the problem of having few training examples for new fine-grained classes. To alleviate this problem, off-the-shelf image…

cs.CV2021

How You Move Your Head Tells What You Do: Self-supervised Video Representation Learning with Egocentric Cameras and IMU Sensors

Satoshi Tsutsui, Ruta Desai, Karl Ridgeway

Understanding users' activities from head-mounted cameras is a fundamental task for Augmented and Virtual Reality (AR/VR) applications. A typical approach is to train a classifier…

cs.CV2021

Reverse-engineer the Distributional Structure of Infant Egocentric Views for Training Generalizable Image Classifiers

Satoshi Tsutsui, David Crandall, Chen Yu

We analyze egocentric views of attended objects from infants. This paper shows 1) empirical evidence that children's egocentric views have more diverse distributions compared to ad…

cs.CV20201 cited

Whose hand is this? Person Identification from Egocentric Hand Gestures

Satoshi Tsutsui, Yanwei Fu, David Crandall

Recognizing people by faces and other biometrics has been extensively studied in computer vision. But these techniques do not work for identifying the wearer of an egocentric (firs…