activity
20242026
most citedHigh-throughput 3D shape completion of potato tubers on a harvester

11 citations · 14 across the 4 of their papers we have counts for

collaborators

5 papers

cs.DL2026

3Dtrees.earth: community research infrastructure for tree and forest analysis using close-range LiDAR data

Janusch Vajna-Jehle, Kilian Gerberding, Daniel Lusk +275

From individual trees to forest stands, three-dimensional structure shapes carbon, water, and energy flows, habitat conditions, and resource availability. Yet tree and forest struc…

cs.CV2026

SPROUT: A Scalable Diffusion Foundation Model for Multi-Crop Plant Phenotyping

Shuai Xiang, James Burridge, Shouyang Liu +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

PointRAFT: 3D deep learning for high-throughput prediction of potato tuber weight from partial point clouds

Pieter M. Blok, Haozhou Wang, Hyun Kwon Suh +3

Potato yield is a key indicator for optimizing cultivation practices in agriculture. Potato yield can be estimated on harvesters using RGB-D cameras, which capture three-dimensiona…

cs.CV2024★ 11 cited

High-throughput 3D shape completion of potato tubers on a harvester

Pieter M. Blok, Federico Magistri, Cyrill Stachniss +3

Potato yield is an important metric for farmers to further optimize their cultivation practices. Potato yield can be estimated on a harvester using an RGB-D camera that can estimat…

cs.CV2024★ 3 cited

DODA: Adapting Object Detectors to Dynamic Agricultural Environments in Real-Time with Diffusion

Shuai Xiang, Pieter M. Blok, James Burridge +2

Object detection has wide applications in agriculture, but domain shifts of diverse environments limit the broader use of the trained models. Existing domain adaptation methods usu…