Papers 3D Open-Vocabulary Instance Segmentation
“3D Open-Vocabulary Instance Segmentation” 태그가 달린 논문 14편 · 필터 해제
NVSMask3D: Hard Visual Prompting with Camera Pose Interpolation for 3D Open Vocabulary Instance Segmentation
Vision-language models (VLMs) have demonstrated impressive zero-shot transfer capabilities in image-level visual perception tasks. However, they fall short in 3D instance-level segmentation tasks that require accurate lo…
3D Instance Segmentation3D Open-Vocabulary Instance SegmentationDescriptiveInstance Segmentation+2Any3DIS: Class-Agnostic 3D Instance Segmentation by 2D Mask Tracking
Existing 3D instance segmentation methods frequently encounter issues with over-segmentation, leading to redundant and inaccurate 3D proposals that complicate downstream tasks. This challenge arises from their unsupervis…
3D Instance Segmentation3D Open-Vocabulary Instance SegmentationInstance SegmentationSegmentation+1Open-YOLO 3D: Towards Fast and Accurate Open-Vocabulary 3D Instance Segmentation
Recent works on open-vocabulary 3D instance segmentation show strong promise, but at the cost of slow inference speed and high computation requirements. This high computation cost is typically due to their heavy reliance…
2D Object Detection3D Instance Segmentation3D Open-Vocabulary Instance SegmentationInstance Segmentation+4OpenDAS: Open-Vocabulary Domain Adaptation for 2D and 3D Segmentation
Recently, Vision-Language Models (VLMs) have advanced segmentation techniques by shifting from the traditional segmentation of a closed-set of predefined object classes to open-vocabulary segmentation (OVS), allowing use…
3D Instance Segmentation3D Open-Vocabulary Instance SegmentationAutonomous DrivingDomain Adaptation+8MaskClustering: View Consensus based Mask Graph Clustering for Open-Vocabulary 3D Instance Segmentation
Open-vocabulary 3D instance segmentation is cutting-edge for its ability to segment 3D instances without predefined categories. However, progress in 3D lags behind its 2D counterpart due to limited annotated 3D data. To …
3D Instance Segmentation3D Open-Vocabulary Instance SegmentationGraph ClusteringInstance Segmentation+5Open3DIS: 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. Objects within 3D environments exhibit diverse shapes, scales, and colors, making precise …
3D Instance Segmentation3D Open-Vocabulary Instance SegmentationInstance SegmentationObject Localization+3OVIR-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. Given a language query, the proposed method is able to return a …
3D Open-Vocabulary Instance SegmentationRegion ProposalRetrievalRobot NavigationOpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation
In this work, we introduce OpenIns3D, a new 3D-input-only framework for 3D open-vocabulary scene understanding. The OpenIns3D framework employs a "Mask-Snap-Lookup" scheme. The "Mask" module learns class-agnostic mask pr…
3D Open-Vocabulary Instance Segmentation3D Open-Vocabulary Object DetectionInstance Segmentationobject-detection+5Lowis3D: Language-Driven Open-World Instance-Level 3D Scene Understanding
Open-world instance-level scene understanding aims to locate and recognize unseen object categories that are not present in the annotated dataset. This task is challenging because the model needs to both localize novel 3…
3D geometry3D Open-Vocabulary Instance SegmentationInstance SegmentationPanoptic Segmentation+4OpenMask3D: Open-Vocabulary 3D Instance Segmentation
We introduce the task of open-vocabulary 3D instance segmentation. Current approaches for 3D instance segmentation can typically only recognize object categories from a pre-defined closed set of classes that are annotate…
3D Instance Segmentation3D Open-Vocabulary Instance SegmentationInstance SegmentationObject+4PLA: Language-Driven Open-Vocabulary 3D Scene Understanding
Open-vocabulary scene understanding aims to localize and recognize unseen categories beyond the annotated label space. The recent breakthrough of 2D open-vocabulary perception is largely driven by Internet-scale paired i…
3D Open-Vocabulary Instance SegmentationContrastive LearningInstance SegmentationRepresentation Learning+2OpenScene: 3D Scene Understanding with Open Vocabularies
Traditional 3D scene understanding approaches rely on labeled 3D datasets to train a model for a single task with supervision. We propose OpenScene, an alternative approach where a model predicts dense features for 3D sc…
3D Open-Vocabulary Instance Segmentation3D Semantic SegmentationScene UnderstandingSemantic SegmentationPointCLIP V2: Prompting CLIP and GPT for Powerful 3D Open-world Learning
Large-scale pre-trained models have shown promising open-world performance for both vision and language tasks. However, their transferred capacity on 3D point clouds is still limited and only constrained to the classific…
3D Classification3D Object Detection3D Open-Vocabulary Instance Segmentation3D Part Segmentation+10PointCLIP: Point Cloud Understanding by CLIP
Recently, zero-shot and few-shot learning via Contrastive Vision-Language Pre-training (CLIP) have shown inspirational performance on 2D visual recognition, which learns to match images with their corresponding texts in …
3D Open-Vocabulary Instance SegmentationFew-Shot LearningOpen Vocabulary Object DetectionTraining-free 3D Part Segmentation+5