An unsupervised approach towards promptable defect segmentation in laser-based additive manufacturing by Segment Anything

7 December 2023

Papers citing "An unsupervised approach towards promptable defect segmentation in laser-based additive manufacturing by Segment Anything"

8 / 8 papers shown

Title
Learning to Prompt Segment Anything Models Jiaxing Huang Kai Jiang Jingyi Zhang Han Qiu Lewei Lu Shijian Lu Eric P. Xing VLM LRM 40 7 0 09 Jan 2024
Foundational Models in Medical Imaging: A Comprehensive Survey and Future Vision Bobby Azad Reza Azad Sania Eskandari Afshin Bozorgpour A. Kazerouni I. Rekik Dorit Merhof VLM MedIm 93 59 0 28 Oct 2023
Caption Anything: Interactive Image Description with Diverse Multimodal Controls Teng Wang Jinrui Zhang Junjie Fei Hao Zheng Yunlong Tang Zhe Li Mingqi Gao Shanshan Zhao MLLM 102 82 0 04 May 2023
Customized Segment Anything Model for Medical Image Segmentation Kaiwen Zhang Dong Liu MedIm VLM 95 286 0 26 Apr 2023
Masked Autoencoders Are Scalable Vision Learners Kaiming He Xinlei Chen Saining Xie Yanghao Li Piotr Dollár Ross B. Girshick ViT TPM 258 7,412 0 11 Nov 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,764 0 24 Feb 2021
Automatic Volumetric Segmentation of Additive Manufacturing Defects with 3D U-Net Vivian Wen Hui Wong M. Ferguson K. Law Y. T. Lee P. Witherell 3DPC 24 19 0 22 Jan 2021
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 232 75,445 0 18 May 2015