1 citations · 1 across the 7 of their papers we have counts for
4 papers · 2 filters
Fi-ImageNet-1k: An OOD Benchmark From the Inside of the ImageNet-1k Validation Set
Ruslan Rozumnyi, Matěj Suchánek, Tomáš Vojíř +2
Out-of-distribution (OOD) detection predicts whether a test image belongs to none of the predefined classes. To evaluate this task, benchmarks need images from outside the in-distr…
Doomed to Re-Annotate, Forever: The ImageNet Story
Illia Volkov, Nikita Kisel, Tetiana Mishkina +2
Top-1 accuracy on ImageNet-1k remains the most commonly reported metric in visual recognition. Quality issues with the dataset have been repeatedly reported, yet the original 2012…
Multimodal Large Language Models as Image Classifiers
Nikita Kisel, Illia Volkov, Klara Janouskova +1
Multimodal Large Language Models (MLLM) classification performance depends critically on evaluation protocol and ground truth quality. Studies comparing MLLMs with supervised and v…
Koo-Fu CLIP: Closed-Form Adaptation of Vision-Language Models via Fukunaga-Koontz Linear Discriminant Analysis
Matej Suchanek, Klara Janouskova, Ondrej Vasatko +1
Visual-language models such as CLIP provide powerful general-purpose representations, but their raw embeddings are not optimized for supervised classification, often exhibiting lim…