Concept
Connected-component labeling
Publications associées (39)
Region Extraction in Mesh Intersection
Annalisa Buffa, Pablo Antolin Sanchez, Emiliano Cirillo
Region extraction is a very common task in both Computer Science and Engineering with several applications in object recognition and motion analysis, among others. Most of the literature focuses on regions delimited by straight lines, often in the special ...
2023Weakly supervised joint whole-slide segmentation and classification in prostate cancer
Maria Gabrani, Guillaume Jaume, Pushpak Pati, Zeineb Ayadi, Kevin Thandiackal
The identification and segmentation of histological regions of interest can provide significant support to pathologists in their diagnostic tasks. However, segmentation methods are constrained by the difficulty in obtaining pixel-level annotations, which a ...
ELSEVIER2023Segmenting Without Annotating: Crack Segmentation and Monitoring via Post-Hoc Classifier Explanations
Devis Tuia, Olga Fink, Florent Evariste Forest, Hugo Laurent Pascal Porta
Monitoring the cracks in walls, roads and other types of infrastructure is essential to ensure the safety of a structure, and plays an important role in structural health monitoring. Automatic visual inspection allows an efficient, costeffective and safe h ...
Research Publishing2023QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval
Shaokai Ye, Yuan He, Hang Su, Jinfeng Li
We study the query-based attack against image retrieval to evaluate its robustness against adversarial examples under the black-box setting, where the adversary only has query access to the top-1 ranked unlabeled images from the database. Compared with que ...
IEEE COMPUTER SOC2021SynDeMo: Synergistic Deep Feature Alignment for Joint Learning of Depth and Ego-Motion
Jean-Philippe Thiran, Mohammad Saeed Rad
Despite well-established baselines, learning of scene depth and ego-motion from monocular video remains an ongoing challenge, specifically when handling scaling ambiguity issues and depth inconsistencies in image sequences. Much prior work uses either a su ...
IEEE COMPUTER SOC2019Learning Monocular 3D Human Pose Estimation from Multi-view Images
Pascal Fua, Mathieu Salzmann, Frédéric Meyer, Isinsu Katircioglu, Helge Jochen Rhodin, Victor Constantin
Accurate 3D human pose estimation from single images is possible with sophisticated deep-net architectures that have been trained on very large datasets. However, this still leaves open the problem of capturing motions for which no such database exists. Ma ...
2018