Titlebook: Computer Vision – ECCV 2024; 18th European Confer Aleš Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

CROW

Rejuan Islam,Anirban Pandey,Tilak Sahaients that enforce the per-point sharing of basis trajectories. By carefully applying a sparsity loss to the motion coefficients, we are able to disentangle the motions that comprise the scene, independently control them, and generate novel motion combinations that have never been seen before. We ca

Mirage

注意

Generosity

PANG

Alternatives to State-Socialism in Britainining, the weights perturbations are maximized on simulated out-of-distribution (OOD) data to heighten the challenge of model theft, while being minimized on in-distribution (ID) training data to preserve model utility. Additionally, we formulate an attack-aware defensive training objective function

车床

,Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays Off,lity, we need reliable methods that can find such adversarial perturbations. For image classification models, evaluation methodologies have emerged that have stood the test of time. However, we argue that in the area of semantic segmentation, a good approximation of the sensitivity to adversarial pe

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,SKYSCENES: A Synthetic Dataset for Aerial Scene Understanding,. Due to inherent challenges in obtaining such images in controlled real-world settings, we present ., a synthetic dataset of densely annotated aerial images captured from Unmanned Aerial Vehicle (UAV) perspectives. We carefully curate . images from . to comprehensively capture diversity across layo

箴言

Large-Scale Multi-hypotheses Cell Tracking Using Ultrametric Contours Maps,cking cells across large microscopy datasets on two fronts: (i) It can solve problems containing millions of segmentation instances in terabyte-scale 3D+t datasets; (ii) It achieves competitive results with or without deep learning, bypassing the requirement of 3D annotated data, that is scarce in t