Published in PeerJ, 2021
A 3D reconstruction and plant analysis paper linking leaf-angle measurements to genetic variation in sorghum.
Recommended citation: Tross, M. C., Gaillard, M., Zwiener, M., Miao, C., Grove, R. J., Li, B., Benes, B., & Schnable, J. C. (2021). "3D Reconstruction Identifies Loci Linked to Variation in Angle of Individual Sorghum Leaves." PeerJ, 9, e12628.
Published in ACM Transactions on Graphics, 2021
A method for reconstructing realistic botanical tree structure from a single image by combining learned priors and procedural growth.
Recommended citation: Li, B., Kaluzny, J., Klein, J., Michels, D. L., Palubicki, W., Benes, B., & Pirk, S. (2021). "Learning to Reconstruct Botanical Trees from Single Images." ACM Transactions on Graphics, 40(6).
Published in IEEE Transactions on Visualization and Computer Graphics, 2023
A learned representation for tree modeling that combines latent structure with context-aware generation.
Recommended citation: Zhou, X., Li, B., Benes, B., Fei, S., & Pirk, S. (2023). "DeepTree: Modeling Trees with Situated Latents." IEEE Transactions on Visualization and Computer Graphics, 1-14.
Published in ACM Transactions on Graphics, 2023
A model for coordinated tree growth above and below ground, linking canopy development with roots, soil, water, and nutrients.
Recommended citation: Li, B., Klein, J., Michels, D. L., Pirk, S., Benes, B., & Palubicki, W. (2023). "Rhizomorph: The Coordinated Function of Shoots and Roots." ACM Transactions on Graphics, 42(4).
Published in ACM Transactions on Graphics, 2023
A transformer-driven approach to tree generation that connects learned latent structure with L-system style procedural representations.
Recommended citation: Lee, J. J., Li, B., & Benes, B. (2023). "Latent L-Systems: Transformer-Based Tree Generator." ACM Transactions on Graphics, 43(1).
Published in Computers and Electronics in Agriculture, 2024
A 3D point-cloud segmentation paper for separating nearby plant organs that share the same semantic class.
Recommended citation: Zarei, A., Li, B., Schnable, J. C., Lyons, E., Pauli, D., Barnard, K., & Benes, B. (2024). "PlantSegNet: 3D Point Cloud Instance Segmentation of Nearby Plant Organs with Identical Semantics." Computers and Electronics in Agriculture, 221, 108922.
Published in The Plant Phenome Journal, 2024
A phenotyping paper using synthetic training data to improve sorghum segmentation and leaf counting.
Recommended citation: Ostermann, I., Benes, B., Gaillard, M., Li, B., Davis, J., Grove, R., Shrestha, N., Tross, M. C., & Schnable, J. C. (2024). "Sorghum Segmentation and Leaf Counting Using In Silico Trained Deep Neural Model." The Plant Phenome Journal, 7(1), e70002.
Published in ACM Transactions on Graphics, 2024
A tree modeling paper on volumetric structure, strands, and interactive control over rich arboreal detail.
Recommended citation: Li, B., Schwarz, N. A., Palubicki, W., Pirk, S., & Benes, B. (2024). "Interactive Invigoration: Volumetric Modeling of Trees with Strands." ACM Transactions on Graphics, 43(4).
Published in Plant Phenomics, 2025
A plant phenotyping study that uses 3D reconstruction to support quantitative analysis of phyllotaxy at scale.
Recommended citation: Davis, J. M., Gaillard, M., Tross, M. C., Shrestha, N., Ostermann, I., Grove, R. J., Li, B., Benes, B., & Schnable, J. C. (2025). "3D Reconstruction Enables High-Throughput Phenotyping and Quantitative Genetic Analysis of Phyllotaxy." Plant Phenomics, 100023.
Published in European Conference on Computer Vision, 2025
A dataset and reconstruction effort that turns single-image tree inputs into simulation-ready assets with diffusion-based priors.
Recommended citation: Lee, J. J., Li, B., Beery, S., Huang, J., Fei, S., Yeh, R. A., & Benes, B. (2025). "Tree-D Fusion: Simulation-Ready Tree Dataset from Single Images with Diffusion Priors." European Conference on Computer Vision, 439-460.
Published in IEEE Transactions on Geoscience and Remote Sensing, 2025
A reconstruction pipeline for forest structure that combines learned ranking with geometric and remote-sensing signals.
Recommended citation: Zhou, X., Li, B., Benes, B., Habib, A., Fei, S., Shao, J., & Pirk, S. (2025). "TreeStructor: Forest Reconstruction With Neural Ranking." IEEE Transactions on Geoscience and Remote Sensing, 63, 1-19.
Published in SIGGRAPH Conference Papers, 2025
An interactive tree modeling paper focused on breakage behavior and strand-based structural control.
Recommended citation: Li, B., Schwarz, N., Palubicki, W., Pirk, S., Michels, D. L., & Benes, B. (2025). "Stressful Tree Modeling: Breaking Branches with Strands." SIGGRAPH Conference Papers.