activity
20202026
most citedCrossmodal Language Grounding in an Embodied Neurocognitive Model

21 citations · 26 across the 8 of their papers we have counts for

collaborators

8 papers

cs.SD2026

Woosh: A Sound Effects Foundation Model

Gaëtan Hadjeres, Marc Ferras, Khaled Koutini +7

The audio research community depends on open generative models as foundational tools for building novel approaches and establishing baselines. In this report, we present Woosh, Son…

cs.CV2024

EgoCVR: An Egocentric Benchmark for Fine-Grained Composed Video Retrieval

Thomas Hummel, Shyamgopal Karthik, Mariana-Iuliana Georgescu +1

In Composed Video Retrieval, a video and a textual description which modifies the video content are provided as inputs to the model. The aim is to retrieve the relevant video with…

cs.CV2023

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…

cs.CV2023

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…

cs.CV2022★ 2 cited

Semantic Image Synthesis with Semantically Coupled VQ-Model

Stephan Alaniz, Thomas Hummel, Zeynep Akata

Semantic image synthesis enables control over unconditional image generation by allowing guidance on what is being generated. We conditionally synthesize the latent space from a ve…

cs.CV2022★ 2 cited

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…

cs.CV2021★ 1 cited

Where and When: Space-Time Attention for Audio-Visual Explanations

Yanbei Chen, Thomas Hummel, A. Sophia Koepke +1

Explaining the decision of a multi-modal decision-maker requires to determine the evidence from both modalities. Recent advances in XAI provide explanations for models trained on s…

cs.NE2020★ 21 cited

Crossmodal Language Grounding in an Embodied Neurocognitive Model

Stefan Heinrich, Yuan Yao, Tobias Hinz +5

Human infants are able to acquire natural language seemingly easily at an early age. Their language learning seems to occur simultaneously with learning other cognitive functions a…