22 citations · 28 across the 8 of their papers we have counts for
6 papers · 1 filter
Audio-Visual Generalized Zero-Shot Learning using Pre-Trained Large Multi-Modal Models
David Kurzendörfer, Otniel-Bogdan Mercea, A. Sophia Koepke +1
Audio-visual zero-shot learning methods commonly build on features extracted from pre-trained models, e.g. video or audio classification models. However, existing benchmarks predat…
Time-, Memory- and Parameter-Efficient Visual Adaptation
Otniel-Bogdan Mercea, Alexey Gritsenko, Cordelia Schmid +1
As foundation models become more popular, there is a growing need to efficiently finetune them for downstream tasks. Although numerous adaptation methods have been proposed, they a…
Video-adverb retrieval with compositional adverb-action embeddings
Thomas Hummel, Otniel-Bogdan Mercea, A. Sophia Koepke +1
Retrieving adverbs that describe an action in a video poses a crucial step towards fine-grained video understanding. We propose a framework for video-to-adverb retrieval (and vice…
Text-to-feature diffusion for audio-visual few-shot learning
Otniel-Bogdan Mercea, Thomas Hummel, A. Sophia Koepke +1
Training deep learning models for video classification from audio-visual data commonly requires immense amounts of labeled training data collected via a costly process. A challengi…
Temporal and cross-modal attention for audio-visual zero-shot learning
Otniel-Bogdan Mercea, Thomas Hummel, A. Sophia Koepke +1
Audio-visual generalised zero-shot learning for video classification requires understanding the relations between the audio and visual information in order to be able to recognise…
Audio-visual Generalised Zero-shot Learning with Cross-modal Attention and Language
Otniel-Bogdan Mercea, Lukas Riesch, A. Sophia Koepke +1
Learning to classify video data from classes not included in the training data, i.e. video-based zero-shot learning, is challenging. We conjecture that the natural alignment betwee…