77 citations · 146 across the 11 of their papers we have counts for
14 papers
Audio-visual Generalized Zero-shot Learning the Easy Way
Shentong Mo, Pedro Morgado
Audio-visual generalized zero-shot learning is a rapidly advancing domain that seeks to understand the intricate relations between audio and visual cues within videos. The overarch…
Unveiling the Power of Audio-Visual Early Fusion Transformers with Dense Interactions through Masked Modeling
Shentong Mo, Pedro Morgado
Humans possess a remarkable ability to integrate auditory and visual information, enabling a deeper understanding of the surrounding environment. This early fusion of audio and vis…
Why Is Prompt Tuning for Vision-Language Models Robust to Noisy Labels?
Cheng-En Wu, Yu Tian, Haichao Yu +4
Vision-language models such as CLIP learn a generic text-image embedding from large-scale training data. A vision-language model can be adapted to a new classification task through…
A Unified Audio-Visual Learning Framework for Localization, Separation, and Recognition
Shentong Mo, Pedro Morgado
The ability to accurately recognize, localize and separate sound sources is fundamental to any audio-visual perception task. Historically, these abilities were tackled separately,…
Learning State-Aware Visual Representations from Audible Interactions
Himangi Mittal, Pedro Morgado, Unnat Jain +1
We propose a self-supervised algorithm to learn representations from egocentric video data. Recently, significant efforts have been made to capture humans interacting with their ow…
A Closer Look at Weakly-Supervised Audio-Visual Source Localization
Shentong Mo, Pedro Morgado
Audio-visual source localization is a challenging task that aims to predict the location of visual sound sources in a video. Since collecting ground-truth annotations of sounding o…