6 papers
A Matched-Budget Audit Framework for Recaptioned Image-Text Supervision Distributions
Giyeong Oh, Junghun Park, Yuhan Bae +1
Recaptioned image-text corpora are now standard for text-to-image (T2I) training, with vision--language model (VLM) captioners replacing sparse alt-text by dense descriptions. A re…
Diffusion-Driven Two-Stage Active Learning for Low-Budget Semantic Segmentation
Jeongin Kim, Wonho Bae, YouLee Han +4
Semantic segmentation demands dense pixel-level annotations, which can be prohibitively expensive - especially under extremely constrained labeling budgets. In this paper, we addre…
InfoCausalQA:Can Models Perform Non-explicit Causal Reasoning Based on Infographic?
Keummin Ka, Junhyeong Park, Jaehyun Jeon +1
Recent advances in Vision-Language Models (VLMs) have demonstrated impressive capabilities in perception and reasoning. However, the ability to perform causal inference -- a core a…
V.I.P. : Iterative Online Preference Distillation for Efficient Video Diffusion Models
Jisoo Kim, Wooseok Seo, Junwan Kim +3
With growing interest in deploying text-to-video (T2V) models in resource-constrained environments, reducing their high computational cost has become crucial, leading to extensive…
ActionSwitch: Class-agnostic Detection of Simultaneous Actions in Streaming Videos
Hyolim Kang, Jeongseok Hyun, Joungbin An +2
Online Temporal Action Localization (On-TAL) is a critical task that aims to instantaneously identify action instances in untrimmed streaming videos as soon as an action concludes…
Layout-and-Retouch: A Dual-stage Framework for Improving Diversity in Personalized Image Generation
Kangyeol Kim, Wooseok Seo, Sehyun Nam +5
Personalized text-to-image (P-T2I) generation aims to create new, text-guided images featuring the personalized subject with a few reference images. However, balancing the trade-of…