3D Instance Segmentation
58 papers with code • 8 benchmarks • 13 datasets
Image: OccuSeg
Benchmarks
These leaderboards are used to track progress in 3D Instance Segmentation
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Libraries
Use these libraries to find 3D Instance Segmentation models and implementations
ScanNet
S3DIS
KITTI-360
PartNet
SceneNN
STPLS3D
ScanNet200
CREMI
FOR-instance
Latest papers with no code
EipFormer: Emphasizing Instance Positions in 3D Instance Segmentation
It enhances the initial instance positions through weighted farthest point sampling and further refines the instance positions and proposals using aggregation averaging and center matching.
Three Ways to Improve Verbo-visual Fusion for Dense 3D Visual Grounding
A common formulation to tackle 3D visual grounding is grounding-by-detection, where localization is done via bounding boxes.
Weakly Supervised 3D Instance Segmentation without Instance-level Annotations
3D semantic scene understanding tasks have achieved great success with the emergence of deep learning, but often require a huge amount of manually annotated training data.
ClickSeg: 3D Instance Segmentation with Click-Level Weak Annotations
Instead of directly using the model inference way, i. e., mean-shift clustering, to generate the pseudo labels, we propose to use k-means with fixed initial seeds: the annotated points.
PSGformer: Enhancing 3D Point Cloud Instance Segmentation via Precise Semantic Guidance
The model achieves a more comprehensive feature representation by the features which connect global and local features.
UnScene3D: Unsupervised 3D Instance Segmentation for Indoor Scenes
We propose UnScene3D, the first fully unsupervised 3D learning approach for class-agnostic 3D instance segmentation of indoor scans.
SUDS: Scalable Urban Dynamic Scenes
We extend neural radiance fields (NeRFs) to dynamic large-scale urban scenes.
OSIS: Efficient One-stage Network for 3D Instance Segmentation
Current 3D instance segmentation models generally use multi-stage methods to extract instance objects, including clustering, feature extraction, and post-processing processes.
The XPRESS Challenge: Xray Projectomic Reconstruction -- Extracting Segmentation with Skeletons
In this task, we provide volumetric XNH images of cortical white matter axons from the mouse brain along with ground truth annotations for axon trajectories.
Query Refinement Transformer for 3D Instance Segmentation
Additionally, we design an affiliated transformer decoder that suppresses the interference of noise background queries and helps the foreground queries focus on instance discriminative parts to predict final segmentation results.
