3 citations · 6 across the 7 of their papers we have counts for
7 papers
FlexLAM: Resolving the Bottleneck Trade-off in Latent Action Learning
Takanori Yoshimoto, Yang Hu, Naruya Kondo +1
Latent actions provide a compact interface between action-free video and downstream decision-making, yet existing Latent Action Models (LAMs) force every transition through a fixed…
Instant Skinned Gaussian Avatars for Web, Mobile and VR Applications
Naruya Kondo, Yuto Asano, Yoichi Ochiai
We present Instant Skinned Gaussian Avatars, a real-time and cross-platform 3D avatar system. Many approaches have been proposed to animate Gaussian Splatting, but they often requi…
From Geometry to Culture: An Iterative VLM Layout Framework for Placing Objects in Complex 3D Scene Contexts
Yuto Asano, Naruya Kondo, Tatsuki Fushimi +1
3D layout tasks have traditionally concentrated on geometric constraints, but many practical applications demand richer contextual understanding that spans social interactions, cul…
Dance Generation by Sound Symbolic Words
Miki Okamura, Naruya Kondo, Tatsuki Fushimi +2
This study introduces a novel approach to generate dance motions using onomatopoeia as input, with the aim of enhancing creativity and diversity in dance generation. Unlike text an…
Towards Digital Nature: Bridging the Gap between Turing Machine Objects and Linguistic Objects in LLMMs for Universal Interaction of Object-Oriented Descriptions
Yoichi Ochiai, Naruya Kondo, Tatsuki Fushimi
In this paper, we propose a novel approach to establish a connection between linguistic objects and classes in Large Language Model Machines (LLMMs) such as GPT3.5 and GPT4, and th…
Deep Billboards towards Lossless Real2Sim in Virtual Reality
Naruya Kondo, So Kuroki, Ryosuke Hyakuta +3
An aspirational goal for virtual reality (VR) is to bring in a rich diversity of real world objects losslessly. Existing VR applications often convert objects into explicit 3D mode…
VaxNeRF: Revisiting the Classic for Voxel-Accelerated Neural Radiance Field
Naruya Kondo, Yuya Ikeda, Andrea Tagliasacchi +3
Neural Radiance Field (NeRF) is a popular method in data-driven 3D reconstruction. Given its simplicity and high quality rendering, many NeRF applications are being developed. Howe…