4 papers
Finding Optimal Video Moment without Training: Gaussian Boundary Optimization for Weakly Supervised Video Grounding
Sunoh Kim, Kimin Yun, Daeho Um
Weakly supervised temporal video grounding aims to localize query-relevant segments in untrimmed videos using only video-sentence pairs, without requiring ground-truth segment anno…
UOD: Unseen Object Detection in 3D Point Cloud
Hyunjun Choi, Daeho Um, Hawook Jeong
Existing 3D object detectors encounter extreme challenges in localizing unseen 3D objects and recognizing them as unseen, which is a crucial technology in autonomous driving in the…
Enhancing Weakly Supervised Video Grounding via Diverse Inference Strategies for Boundary and Prediction Selection
Sunoh Kim, Daeho Um
Weakly supervised video grounding aims to localize temporal boundaries relevant to a given query without explicit ground-truth temporal boundaries. While existing methods primarily…
RoCOCO: Robustness Benchmark of MS-COCO to Stress-test Image-Text Matching Models
Seulki Park, Daeho Um, Hajung Yoon +3
With the extensive use of vision-language models in various downstream tasks, evaluating their robustness is crucial. In this paper, we propose a benchmark for assessing the robust…