86 papers
This paper addresses the unexplored challenge of label noise in action-based video object segmentation by introducing the ActiSeg-NL benchmark, analyzing the impact of textual and mask annotation noise, and proposing a Parallel Mask Head Mechanism to enhance robustness for embodied intelligence applications.
This paper introduces Fast Equivariant Imaging (FEI), a novel unsupervised learning framework that leverages the Augmented Lagrangian method and auxiliary Plug-and-Play denoisers to achieve a 10x training acceleration and improved generalization for deep imaging tasks like X-ray CT reconstruction and inpainting without requiring ground-truth data.
This paper introduces Implicit U-KAN 2.0, a novel medical image segmentation model that combines second-order neural ordinary differential equations (SONO) with MultiKAN layers in a two-phase encoder-decoder architecture to achieve superior performance, enhanced interpretability, and dimension-independent approximation capabilities while reducing computational costs.
GeoTop is a mathematically principled framework that unifies Topological Data Analysis and Lipschitz-Killing Curvatures to resolve the diagnostic ambiguity of topologically equivalent structures by integrating robust topological signatures with precise geometric features, thereby achieving superior accuracy and interpretability in image classification tasks such as skin lesion diagnosis.
This dissertation presents a comprehensive field imaging framework that leverages advanced computer vision algorithms, including 2D instance segmentation and an integrated 3D reconstruction-segmentation-completion approach, to overcome the limitations of traditional methods and enable accurate morphological characterization of construction aggregates across diverse field scenarios.
Cryo-SWAN is a multi-scale wavelet-decomposition-inspired variational autoencoder that effectively learns robust 3D molecular density representations from voxelized data, outperforming state-of-the-art methods in reconstruction quality and enabling advanced applications like denoising and conditional shape generation for structural biology.