3 papers
cs.CV2026
SPROUT: A Scalable Diffusion Foundation Model for Agricultural Vision
Shuai Xiang, Wei Guo, James Burridge +4
Image-based plant phenotyping depends on dense structural understanding of crops, yet pixel-level annotation remains expensive across species, organs, growth stages, and field cond…
cs.CV2025
TasselNetV4: A vision foundation model for cross-scene, cross-scale, and cross-species plant counting
Xiaonan Hu, Xuebing Li, Jinyu Xu +8
Accurate plant counting provides valuable information for agriculture such as crop yield prediction, plant density assessment, and phenotype quantification. Vision-based approaches…
eess.IV2025
Global Rice Multi-Class Segmentation Dataset (RiceSEG): A Comprehensive and Diverse High-Resolution RGB-Annotated Images for the Development and Benchmarking of Rice Segmentation Algorithms
Junchi Zhou, Haozhou Wang, Yoichiro Kato +21
Developing computer vision-based rice phenotyping techniques is crucial for precision field management and accelerating breeding, thereby continuously advancing rice production. Am…