Segment and Edit Anything in 3D Scenes with Identity-Aware Gaussian Splatting
GaussianGrouping is a pioneering open-source framework that extends 3D Gaussian Splatting (3DGS) to enable joint 3D reconstruction and multi-object segmentation. By introducing 'Identity Encoding'—a learnable parameter assigned to each Gaussian—the system maps 3D points to specific object identities supervised by 2D masks from the Segment Anything Model (SAM). In the 2026 market landscape, GaussianGrouping has transitioned from a research breakthrough to a foundational layer for industrial digital twins and real-time VFX pipelines. Its technical architecture utilizes a grouping loss function that enforces spatial and semantic consistency across diverse viewpoints, allowing for the precise isolation of 3D objects within complex scenes. Unlike traditional NeRF-based methods which struggle with discrete object boundaries, GaussianGrouping provides an explicit, point-based representation that supports real-time manipulation, such as object removal, transformation, and recoloring. This makes it an essential tool for developers building autonomous robotic environments and immersive spatial computing applications where granular scene understanding is as critical as visual fidelity.
Assigns a high-dimensional vector to each 3D Gaussian to represent object membership.
Real-time neural rendering and 3D reconstruction in seconds using multi-resolution hash encoding.
Physically-based shading integration for high-fidelity 3D Gaussian Splatting and reflective indoor scene reconstruction.
High-fidelity neural surface reconstruction for turning 2D video into detailed 3D digital twins.
SOTA 3D human pose and shape estimation for real-time digital twin synthesis.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Leverages 2D Foundation Models to provide zero-shot segmentation labels during 3D training.
A lightweight MLP trained alongside Gaussians to decode Identity Encodings into object masks.
Dynamic filtering of Gaussians based on Identity ID during the rasterization phase.
Fills occluded regions by optimizing background Gaussians to occupy empty space left by removed objects.
Maintains the 3DGS advantage of 100+ FPS rendering speeds on consumer GPUs.
Enforces that a 3D point belongs to the same object regardless of the camera angle.
Manually removing an actor or object from a video plate is time-consuming and prone to artifacts.
Registry Updated:2/7/2026
Render out the cleaned plate.
Robots struggle to distinguish separate objects in a cluttered bin from raw point clouds.
Existing virtual tours are static; furniture cannot be easily moved or replaced.