4 accepted papers
Symmetry detection is a fundamental problem in computer vision, and symmetries serve as powerful priors for downstream tasks. However, existing learning-based methods for detecting 3D symmetries from single images have been almost exclusively trained and evaluated on object-centric or synthetic data
With diffusion models demonstrating superior capabilities in image editing, more users now rely on online servers for content manipulation via textual prompts rather than traditional offline tools. Despite servers attempting to prevent the proliferation of maliciously edited content via active defen
Accurate 3D reconstruction is frequently hindered by visual aliasing, where visually similar but distinct surfaces (aka, doppelgangers), are incorrectly matched. These spurious matches distort the structure-from-motion (SfM) process, leading to misplaced model elements and reduced accuracy. Prior ef…
We develop a theory for the representation of opaque solids as volumes. Starting from a stochastic representation of opaque solids as random indicator functions we prove the conditions under which such solids can be modeled using exponential volumetric transport. We also derive expressions for the v…