Papers 3D Part Segmentation
“3D Part Segmentation” 태그가 달린 논문 109편 · 필터 해제
SegviGen: Repurposing 3D Generative Model for Part Segmentation
We introduce SegviGen, a framework that repurposes native 3D generative models for 3D part segmentation. Existing pipelines either lift strong 2D priors into 3D via distillation or multi-view mask aggregation, often suff…
3D Part SegmentationPatchAlign3D: Local Feature Alignment for Dense 3D Shape understanding
Current foundation models for 3D shapes excel at global tasks (retrieval, classification) but transfer poorly to local part-level reasoning. Recent approaches leverage vision and language foundation models to directly so…
3D Part SegmentationPrompt EngineeringPoint CloudsName That Part: 3D Part Segmentation and Naming
We address semantic 3D part segmentation: decomposing objects into parts with meaningful names. While datasets exist with part annotations, their definitions are inconsistent across datasets, limiting robust training. Pr…
3D Part SegmentationSegGraph: Leveraging Graphs of SAM Segments for Few-Shot 3D Part Segmentation
This work presents a novel framework for few-shot 3D part segmentation. Recent advances have demonstrated the significant potential of 2D foundation models for low-shot 3D part segmentation. However, it is still an open …
3D Part SegmentationGraph Neural Networksim2art: Accurate Articulated Object Modeling from a Single Video using Synthetic Training Data Only
Understanding articulated objects from monocular video is a crucial yet challenging task in robotics and digital twin creation. Existing methods often rely on complex multi-view setups, high-fidelity object scans, or fra…
3D Part SegmentationDomain AdaptationTEXTRIX: Latent Attribute Grid for Native Texture Generation and Beyond
Prevailing 3D texture generation methods, which often rely on multi-view fusion, are frequently hindered by inter-view inconsistencies and incomplete coverage of complex surfaces, limiting the fidelity and completeness o…
3D Part SegmentationPinPoint3D: Fine-Grained 3D Part Segmentation from a Few Clicks
Fine-grained 3D part segmentation is crucial for enabling embodied AI systems to perform complex manipulation tasks, such as interacting with specific functional components of an object. However, existing interactive seg…
Interactive Segmentation3D Part SegmentationPoint CloudsP3-SAM: Native 3D Part Segmentation
Segmenting 3D assets into their constituent parts is crucial for enhancing 3D understanding, facilitating model reuse, and supporting various applications such as part generation. However, current methods face limitation…
Interactive SegmentationInstance Segmentation3D Part SegmentationGeoSAM2: Unleashing the Power of SAM2 for 3D Part Segmentation
We introduce GeoSAM2, a prompt-controllable framework for 3D part segmentation that casts the task as multi-view 2D mask prediction. Given a textureless object, we render normal and point maps from predefined viewpoints …
3D Part SegmentationPARTE: Part-Guided Texturing for 3D Human Reconstruction from a Single Image
The misaligned human texture across different human parts is one of the main limitations of existing 3D human reconstruction methods. Each human part, such as a jacket or pants, should maintain a distinct texture without…
3D Human Reconstruction3D Part SegmentationImage GenerationHoloPart: Generative 3D Part Amodal Segmentation
3D part amodal segmentation--decomposing a 3D shape into complete, semantically meaningful parts, even when occluded--is a challenging but crucial task for 3D content creation and understanding. Existing 3D part segmenta…
3D geometry3D Part SegmentationSegmentationOpen-Vocabulary Semantic Part Segmentation of 3D Human
3D part segmentation is still an open problem in the field of 3D vision and AR/VR. Due to limited 3D labeled data, traditional supervised segmentation methods fall short in generalizing to unseen shapes and categories. R…
3D Part SegmentationSegmentationAdaCrossNet: Adaptive Dynamic Loss Weighting for Cross-Modal Contrastive Point Cloud Learning
Manual annotation of large-scale point cloud datasets is laborious due to their irregular structure. While cross-modal contrastive learning methods such as CrossPoint and CrossNet have progressed in utilizing multimodal …
3D Part Segmentation3D Point Cloud Classification3D Point Cloud Linear ClassificationContrastive Learning+1Rethinking Masked Representation Learning for 3D Point Cloud Understanding
Self-supervised point cloud representation learning aims to acquire robust and general feature representations from unlabeled data. Recently, masked point modeling-based methods have shown significant performance improve…
3D Part Segmentation3D Point Cloud ClassificationFew-Shot 3D Point Cloud ClassificationRepresentation Learning3D Part Segmentation via Geometric Aggregation of 2D Visual Features
Supervised 3D part segmentation models are tailored for a fixed set of objects and parts, limiting their transferability to open-set, real-world scenarios. Recent works have explored vision-language models (VLMs) as a pr…
3D geometry3D Part SegmentationPrompt EngineeringFind Any Part in 3D
Why don't we have foundation models in 3D yet? A key limitation is data scarcity. For 3D object part segmentation, existing datasets are small in size and lack diversity. We show that it is possible to break this data ba…
3D Part SegmentationDiversityObjectSegmentationSAMPart3D: Segment Any Part in 3D Objects
3D part segmentation is a crucial and challenging task in 3D perception, playing a vital role in applications such as robotics, 3D generation, and 3D editing. Recent methods harness the powerful Vision Language Models (V…
3D Generation3D Part SegmentationInteractive SegmentationKnowledge Distillation+1Beyond local patches: Preserving global–local interactions by enhancing self-attention via 3D point cloud tokenization
Transformer-based architectures have recently shown impressive performance on various point cloud understanding tasks such as 3D object shape classification and semantic segmentation. Particularly, this can be attributed…
3D Classification3D Object Classification3D Part Segmentation3D Point Cloud Classification+3Search3D: Hierarchical Open-Vocabulary 3D Segmentation
Open-vocabulary 3D segmentation enables exploration of 3D spaces using free-form text descriptions. Existing methods for open-vocabulary 3D instance segmentation primarily focus on identifying object-level instances but …
3D Instance Segmentation3D Part SegmentationInstance SegmentationObject+33D-JEPA: A Joint Embedding Predictive Architecture for 3D Self-Supervised Representation Learning
Invariance-based and generative methods have shown a conspicuous performance for 3D self-supervised representation learning (SSRL). However, the former relies on hand-crafted data augmentations that introduce bias not un…
3D Part Segmentation3D Point Cloud ClassificationDecoderFew-Shot 3D Point Cloud Classification+1