8 citations · 12 across the 10 of their papers we have counts for
4 papers · 1 filter
The BRAVO Semantic Segmentation Challenge Results in UNCV2024
Tuan-Hung Vu, Eduardo Valle, Andrei Bursuc +16
We propose the unified BRAVO challenge to benchmark the reliability of semantic segmentation models under realistic perturbations and unknown out-of-distribution (OOD) scenarios. W…
WildFusion: Individual Animal Identification with Calibrated Similarity Fusion
Vojtěch Cermak, Lukas Picek, Lukáš Adam +2
We propose a new method - WildFusion - for individual identification of a broad range of animal species. The method fuses deep scores (e.g., MegaDescriptor or DINOv2) and local mat…
PixOOD: Pixel-Level Out-of-Distribution Detection
Tomáš Vojíř, Jan Šochman, Jiří Matas
We propose a dense image prediction out-of-distribution detection algorithm, called PixOOD, which does not require training on samples of anomalous data and is not designed for a s…
Dense Matchers for Dense Tracking
Tomáš Jelínek, Jonáš Šerých, Jiří Matas
Optical flow is a useful input for various applications, including 3D reconstruction, pose estimation, tracking, and structure-from-motion. Despite its utility, the field of dense…