2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2025
Training-free Neural Architecture Search through Variance of Knowledge of Deep Network Weights
Ondřej Týbl, Lukáš Neumann
Deep learning has revolutionized computer vision, but it achieved its tremendous success using deep network architectures which are mostly hand-crafted and therefore likely subopti…
cs.CV2024★ 2 cited
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…
cs.CV2024
Animal Identification with Independent Foreground and Background Modeling
Lukas Picek, Lukas Neumann, Jiri Matas
We propose a method that robustly exploits background and foreground in visual identification of individual animals. Experiments show that their automatic separation, made easy wit…