8 citations · 12 across the 10 of their papers we have counts for
10 papers · 1 filter
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…
LPOSS: Label Propagation Over Patches and Pixels for Open-vocabulary Semantic Segmentation
Vladan Stojnić, Yannis Kalantidis, Jiří 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 Stojnić, 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…
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…
Improving 2D Human Pose Estimation in Rare Camera Views with Synthetic Data
Miroslav Purkrabek, Jiri Matas
Methods and datasets for human pose estimation focus predominantly on side- and front-view scenarios. We overcome the limitation by leveraging synthetic data and introduce RePoGen…
Matching with AffNet based rectifications
Václav Vávra, Dmytro Mishkin, Jiří Matas
We consider the problem of two-view matching under significant viewpoint changes with view synthesis. We propose two novel methods, minimizing the view synthesis overhead. The firs…
FEAR: Fast, Efficient, Accurate and Robust Visual Tracker
Vasyl Borsuk, Roman Vei, Orest Kupyn +3
We present FEAR, a family of fast, efficient, accurate, and robust Siamese visual trackers. We present a novel and efficient way to benefit from dual-template representation for ob…