Grow with the Flow: 4D Reconstruction of Growing Plants with Gaussian Flow Fields

TL;DR

GrowFlow introduces a novel continuous-time 4D plant modeling method using Gaussian primitives and neural ODEs, enabling realistic, temporally consistent visualization of plant growth from multi-view timelapse data.

Contribution

It couples Gaussian primitives with neural ODEs to model nonlinear plant growth as a continuous flow, providing the first temporally coherent 4D representation of growing plants.

Findings

Achieves superior image quality and geometric coherence.

Provides the first temporally consistent 4D plant model.

Effectively reconstructs developmental history in reverse.

Abstract

Modeling the time-varying 3D appearance of plants during growth poses unique challenges: unlike most dynamic scenes, plants continuously generate new geometry as they expand, branch, and differentiate. Existing dynamic scene representations are ill-suited to this setting: deformation fields provide insufficient constraints to yield physically plausible scene dynamics, and 4D Gaussian splatting represents the same physical structures with different Gaussian primitives at different times, breaking temporal consistency. We introduce GrowFlow, a dynamic representation that couples 3D Gaussian primitives with a neural ordinary differential equation to model plant growth as a continuous flow field over geometric parameters (position, scale, and orientation). Our representation enables consistent appearance rendering and models nonlinear, continuous-time growth dynamics with full temporal correspondences for every primitive. To initialize a sufficient set of Gaussian primitives, we first reconstruct the mature plant and then learn a reverse-growth process, effectively simulating the plant's developmental history in reverse. GrowFlow achieves superior image quality and geometric coherence compared to prior methods on a new, multi-view timelapse dataset of plant growth, and provides the first temporally coherent representation for appearance modeling of growing 3D structures.