SOTAVerified

3D Open-Vocabulary Instance Segmentation

Open-vocabulary 3D instance segmentation is a computer vision task that involves identifying and delineating individual objects or instances within a three-dimensional (3D) scene without prior knowledge of a fixed set of object classes or categories. In other words, it extends traditional instance segmentation to a scenario where the number and types of objects present in the 3D environment are not predefined or limited to a specific vocabulary.

Papers

Showing 110 of 14 papers

TitleStatusHype
NVSMask3D: Hard Visual Prompting with Camera Pose Interpolation for 3D Open Vocabulary Instance Segmentation0
Any3DIS: Class-Agnostic 3D Instance Segmentation by 2D Mask Tracking0
Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance SegmentationCode3
OpenDAS: Open-Vocabulary Domain Adaptation for 2D and 3D Segmentation0
MaskClustering: View Consensus based Mask Graph Clustering for Open-Vocabulary 3D Instance Segmentation0
Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask GuidanceCode1
OVIR-3D: Open-Vocabulary 3D Instance Retrieval Without Training on 3D DataCode1
OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance SegmentationCode2
Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding0
OpenMask3D: Open-Vocabulary 3D Instance SegmentationCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Open-YOLO 3DmAP23.7Unverified
2OpenIns3D (with rgbd)mAP21.1Unverified
3Open3DISmAP18.1Unverified
4OpenIns3DmAP15.4Unverified
5OpenMask3DmAP13.1Unverified
6OVIR-3DmAP11.1Unverified
7OpenScene + Mask3DmAP10.9Unverified