Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision最新文献_第2页

Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction. 基于保形预测的逆问题任务驱动不确定性量化。

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2025-01-01 Epub Date: 2024-11-26 DOI: 10.1007/978-3-031-73027-6_11

Jeffrey Wen, Rizwan Ahmad, Philip Schniter

{"title":"Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction.","authors":"Jeffrey Wen, Rizwan Ahmad, Philip Schniter","doi":"10.1007/978-3-031-73027-6_11","DOIUrl":"10.1007/978-3-031-73027-6_11","url":null,"abstract":"In imaging inverse problems, one seeks to recover an image from missing/corrupted measurements. Because such problems are ill-posed, there is great motivation to quantify the uncertainty induced by the measurement-and-recovery process. Motivated by applications where the recovered image is used for a downstream task, such as soft-output classification, we propose a task-centered approach to uncertainty quantification. In particular, we use conformal prediction to construct an interval that is guaranteed to contain the task output from the true image up to a user-specified probability, and we use the width of that interval to quantify the uncertainty contributed by measurement-and-recovery. For posterior-sampling-based image recovery, we construct locally adaptive prediction intervals. Furthermore, we propose to collect measurements over multiple rounds, stopping as soon as the task uncertainty falls below an acceptable level. We demonstrate our methodology on accelerated magnetic resonance imaging (MRI): https://github.com/jwen307/TaskUQ.","PeriodicalId":72676,"journal":{"name":"Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision","volume":"15118 ","pages":"182-199"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109201/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144175722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Semi-supervised Segmentation of Histopathology Images with Noise-Aware Topological Consistency. 具有噪声感知拓扑一致性的组织病理图像半监督分割。

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2024-01-01 Epub Date: 2024-10-25 DOI: 10.1007/978-3-031-73229-4_16

Meilong Xu, Xiaoling Hu, Saumya Gupta, Shahira Abousamra, Chao Chen

{"title":"Semi-supervised Segmentation of Histopathology Images with Noise-Aware Topological Consistency.","authors":"Meilong Xu, Xiaoling Hu, Saumya Gupta, Shahira Abousamra, Chao Chen","doi":"10.1007/978-3-031-73229-4_16","DOIUrl":"10.1007/978-3-031-73229-4_16","url":null,"abstract":"In digital pathology, segmenting densely distributed objects like glands and nuclei is crucial for downstream analysis. Since detailed pixel-wise annotations are very time-consuming, we need semi-supervised segmentation methods that can learn from unlabeled images. Existing semi-supervised methods are often prone to topological errors, e.g., missing or incorrectly merged/separated glands or nuclei. To address this issue, we propose TopoSemiSeg, the first semi-supervised method that learns the topological representation from unlabeled histopathology images. The major challenge is for unlabeled images; we only have predictions carrying noisy topology. To this end, we introduce a noise-aware topological consistency loss to align the representations of a teacher and a student model. By decomposing the topology of the prediction into signal topology and noisy topology, we ensure that the models learn the true topological signals and become robust to noise. Extensive experiments on public histopathology image datasets show the superiority of our method, especially on topology-aware evaluation metrics. Code is available at https://github.com/Melon-Xu/TopoSemiSeg.","PeriodicalId":72676,"journal":{"name":"Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision","volume":"15136 ","pages":"271-289"},"PeriodicalIF":0.0,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12185923/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144487330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dual-Stream Knowledge-Preserving Hashing for Unsupervised Video Retrieval 面向无监督视频检索的双流知识保持哈希算法

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2023-10-12 DOI: 10.1007/978-3-031-19781-9_11

P. Li, Hongtao Xie, Jiannan Ge, Lei Zhang, Shaobo Min, Yongdong Zhang

引用次数: 9

Spatial and Visual Perspective-Taking via View Rotation and Relation Reasoning for Embodied Reference Understanding 通过视角旋转和关系推理的空间和视觉视角获取对具体化参考理解的影响

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2023-09-03 DOI: 10.1007/978-3-031-20059-5_12

Cheng Shi, Sibei Yang

引用次数: 5

Rethinking Confidence Calibration for Failure Prediction 失效预测置信度校准的再思考

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2023-03-06 DOI: 10.1007/978-3-031-19806-9_30

Fei Zhu, Zhen Cheng, Xu-Yao Zhang, Cheng-Lin Liu

引用次数: 11

PCR-CG: Point Cloud Registration via Deep Explicit Color and Geometry PCR-CG:点云配准通过深显色和几何

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2023-02-28 DOI: 10.1007/978-3-031-20080-9_26

Yu Zhang, Junle Yu, Xiaolin Huang, Wenhui Zhou, Ji Hou

引用次数: 7

Diverse Human Motion Prediction Guided by Multi-level Spatial-Temporal Anchors 基于多层次时空锚点的多种人体运动预测

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2023-02-09 DOI: 10.1007/978-3-031-20047-2_15

Sirui Xu, Yu-Xiong Wang, Liangyan Gui

引用次数: 15

Bridging Images and Videos: A Simple Learning Framework for Large Vocabulary Video Object Detection 桥接图像和视频:一个用于大词汇视频对象检测的简单学习框架

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2022-12-20 DOI: 10.1007/978-3-031-19806-9_14

Sanghyun Woo, KwanYong Park, Seoung Wug Oh, In-So Kweon, Joon-Young Lee

引用次数: 3

Union-Set Multi-source Model Adaptation for Semantic Segmentation 基于联合集的多源模型自适应语义分割

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2022-12-06 DOI: 10.1007/978-3-031-19818-2_33

Zongyao Li, Ren Togo, Takahiro Ogawa, M. Haseyama

引用次数: 2

Interclass Prototype Relation for Few-Shot Segmentation 基于类间原型关系的少镜头分割

Computer vision - ECCV ... : ... European Conference on Computer Vision : proceedings. European Conference on Computer Vision Pub Date : 2022-11-16 DOI: 10.1007/978-3-031-19818-2_21

A. Okazawa

引用次数: 9