7 papers
LPOSS: Label Propagation Over Patches and Pixels for Open-vocabulary Semantic Segmentation
Vladan StojniÄ, Yannis Kalantidis, JiÅÃ Matas +1
We propose a training-free method for open-vocabulary semantic segmentation using Vision-and-Language Models (VLMs). Our approach enhances the initial per-patch predictions of VLMs…
ILIAS: Instance-Level Image retrieval At Scale
Giorgos Kordopatis-Zilos, Vladan StojniÄ, Anna Manko +7
This work introduces ILIAS, a new test dataset for Instance-Level Image retrieval At Scale. It is designed to evaluate the ability of current and future foundation models and retri…
Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge
Adam Schmidt, Mert Asim Karaoglu, Soham Sinha +37
Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-b…
PixOOD: Pixel-Level Out-of-Distribution Detection
Tomáš VojÃÅ, Jan Å ochman, JiÅà 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…
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
VojtÄch 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…