3D Open-Vocabulary Instance Segmentation
8 papers with code • 4 benchmarks • 4 datasets
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.
S3DIS
Replica
STPLS3D
ScanNet200
Most implemented papers
PointCLIP: Point Cloud Understanding by CLIP
zrrskywalker/pointclip
•
•
CVPR 2022
On top of that, we design an inter-view adapter to better extract the global feature and adaptively fuse the few-shot knowledge learned from 3D into CLIP pre-trained in 2D.
PointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning
yangyangyang127/pointclip_v2
•
•
ICCV 2023
In this paper, we first collaborate CLIP and GPT to be a unified 3D open-world learner, named as PointCLIP V2, which fully unleashes their potential for zero-shot 3D classification, segmentation, and detection.
OpenScene: 3D Scene Understanding with Open Vocabularies
pengsongyou/openscene
•
•
CVPR 2023
Traditional 3D scene understanding approaches rely on labeled 3D datasets to train a model for a single task with supervision.
PLA: Language-Driven Open-Vocabulary 3D Scene Understanding
Open-vocabulary scene understanding aims to localize and recognize unseen categories beyond the annotated label space.
OpenMask3D: Open-Vocabulary 3D Instance Segmentation
OpenMask3D/openmask3d
•
•
NeurIPS 2023
In this work, we address this limitation, and propose OpenMask3D, which is a zero-shot approach for open-vocabulary 3D instance segmentation.
OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation
When integrated with powerful 2D open-world models such as ODISE and GroundingDINO, excellent results were observed on open-vocabulary instance segmentation.
OVIR-3D: Open-Vocabulary 3D Instance Retrieval Without Training on 3D Data
This work presents OVIR-3D, a straightforward yet effective method for open-vocabulary 3D object instance retrieval without using any 3D data for training.
Open3DIS: Open-Vocabulary 3D Instance Segmentation with 2D Mask Guidance
We introduce Open3DIS, a novel solution designed to tackle the problem of Open-Vocabulary Instance Segmentation within 3D scenes.
