1 citations · 1 across the 3 of their papers we have counts for
5 papers
Interaction-via-Actions: Cattle Interaction Detection with Joint Learning of Action-Interaction Latent Space
Ren Nakagawa, Yang Yang, Risa Shinoda +4
This paper introduces a method and application for automatically detecting behavioral interactions between grazing cattle from a single image, which is essential for smart livestoc…
GaussianPlant: Structure-aligned Gaussian Splatting for 3D Reconstruction of Plants
Yang Yang, Risa Shinoda, Hiroaki Santo +1
We present a method for jointly recovering the appearance and internal structure of botanical plants from multi-view images based on 3D Gaussian Splatting (3DGS). While 3DGS exhibi…
Zero-shot Hierarchical Plant Segmentation via Foundation Segmentation Models and Text-to-image Attention
Junhao Xing, Ryohei Miyakawa, Yang Yang +5
Foundation segmentation models achieve reasonable leaf instance extraction from top-view crop images without training (i.e., zero-shot). However, segmenting entire plant individual…
NeuraLeaf: Neural Parametric Leaf Models with Shape and Deformation Disentanglement
Yang Yang, Dongni Mao, Hiroaki Santo +2
We develop a neural parametric model for 3D leaves for plant modeling and reconstruction that are essential for agriculture and computer graphics. While neural parametric models ar…
Real-Time Cattle Interaction Recognition via Triple-stream Network
Yang Yang, Mizuka Komatsu, Kenji Oyama +1
In stockbreeding of beef cattle, computer vision-based approaches have been widely employed to monitor cattle conditions (e.g. the physical, physiology, and health). To this end, t…