Empowering large language models with 3D point cloud understanding, accompanied by a novel dataset and carefully designed benchmarks. Project page: this https URL* 相关: github.com/OpenRobotLab* 题目: Decoupled Local Aggregation for Point Cloud Learning* PDF: arxiv.org/abs/2308.1653* 作者: ...
* 题目: Diffusion Models for Zero-Shot Open-Vocabulary Segmentation* PDF: arxiv.org/abs/2306.0931* 作者: Laurynas Karazija,Iro Laina,Andrea Vedaldi,Christian Rupprecht* 其他: Project page this https URL* 题目: Robustness Analysis on Foundational Segmentation Models* PDF: arxiv.org/abs/2306.0927*...
3D city models3D model segmentationCityGML3D city model is a virtual representation of a city or urban environment, where in GIS related context, represents existing cities in the world. Initially, they are used only as presentations that complement the results of 2D analyses and bear no ...
Papaleo, L., De Floriani, L. (2009). Semantic-Based Segmentation and Annotation of 3D Models. In: Foggia, P., Sansone, C., Vento, M. (eds) Image Analysis and Processing – ICIAP 2009. ICIAP 2009. Lecture Notes in Computer Science, vol 5716. Springer, Berlin, Heidelberg. https://d...
Medical Imaging Deep Learning library to train and deploy 3D segmentation models on Azure Machine Learning - microsoft/InnerEye-DeepLearning
The official implementation of "3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds". (CVPR 2023) 🔥🔥🔥 🔥 For more information follow thePAPERlink!:fire: Authors:Aoran Xiao,Jiaxing Huang,Weihao Xuan, Ruijie Ren,Kangcheng Liu,Dayan Guan,Abdul...
Segmentation of building models from dense 3D point-cloudsJoachimBauer∗, Konrad Karner∗, Konrad Schindler†,Andreas Klaus∗, Chri..
In the field of construction, synthetic images have been used in tasks such as object detection (including defect detection), semantic segmentation and indoor localisation where they were generated either with the help of 3D models, image augmentation or image-to-image translation using GANs. For ...
Generalizable 3D part segmentation is important but challenging in vision and robotics. Training deep models via conventional supervised methods requires large-scale 3D datasets with fine-grained part annotations, which are costly to collect. This paper explores an alternative way for low-shot part segm...
Paper tables with annotated results for Dual-Teacher Ensemble Models with Double-Copy-Paste for 3D Semi-Supervised Medical Image Segmentation