4 papers
SOUPLE: Enhancing Audio-Visual Localization and Segmentation with Learnable Prompt Contexts
Khanh Binh Nguyen, Chae Jung Park
Large-scale pre-trained image-text models exhibit robust multimodal representations, yet applying the Contrastive Language-Image Pre-training (CLIP) model to audio-visual localizat…
Symmetric masking strategy enhances the performance of Masked Image Modeling
Khanh-Binh Nguyen, Chae Jung Park
Masked Image Modeling (MIM) is a technique in self-supervised learning that focuses on acquiring detailed visual representations from unlabeled images by estimating the missing pix…
SAVE: Segment Audio-Visual Easy way using Segment Anything Model
Khanh-Binh Nguyen, Chae Jung Park
The primary aim of Audio-Visual Segmentation (AVS) is to precisely identify and locate auditory elements within visual scenes by accurately predicting segmentation masks at the pix…
Retro: Reusing teacher projection head for efficient embedding distillation on Lightweight Models via Self-supervised Learning
Khanh-Binh Nguyen, Chae Jung Park
Self-supervised learning (SSL) is gaining attention for its ability to learn effective representations with large amounts of unlabeled data. Lightweight models can be distilled fro…