1 citations · 1 across the 5 of their papers we have counts for
5 papers
Can LLMs Deceive CLIP? Benchmarking Adversarial Compositionality of Pre-trained Multimodal Representation via Text Updates
Jaewoo Ahn, Heeseung Yun, Dayoon Ko +1
While pre-trained multimodal representations (e.g., CLIP) have shown impressive capabilities, they exhibit significant compositional vulnerabilities leading to counterintuitive jud…
ReSpec: Relevance and Specificity Grounded Online Filtering for Learning on Video-Text Data Streams
Chris Dongjoo Kim, Jihwan Moon, Sangwoo Moon +7
The rapid growth of video-text data presents challenges in storage and computation during training. Online learning, which processes streaming data in real-time, offers a promising…
Sample Selection via Contrastive Fragmentation for Noisy Label Regression
Chris Dongjoo Kim, Sangwoo Moon, Jihwan Moon +2
As with many other problems, real-world regression is plagued by the presence of noisy labels, an inevitable issue that demands our attention. Fortunately, much real-world data oft…
Spherical World-Locking for Audio-Visual Localization in Egocentric Videos
Heeseung Yun, Ruohan Gao, Ishwarya Ananthabhotla +6
Egocentric videos provide comprehensive contexts for user and scene understanding, spanning multisensory perception to behavioral interaction. We propose Spherical World-Locking (S…
Dense 2D-3D Indoor Prediction with Sound via Aligned Cross-Modal Distillation
Heeseung Yun, Joonil Na, Gunhee Kim
Sound can convey significant information for spatial reasoning in our daily lives. To endow deep networks with such ability, we address the challenge of dense indoor prediction wit…