21 citations · 33 across the 10 of their papers we have counts for
25 papers · 1 filter
Is user feedback always informative? Retrieval Latent Defending for Semi-Supervised Domain Adaptation without Source Data
Junha Song, Tae Soo Kim, Junha Kim +3
This paper aims to adapt the source model to the target environment, leveraging small user feedback (i.e., labeled target data) readily available in real-world applications. We fin…
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…
VEGS: View Extrapolation of Urban Scenes in 3D Gaussian Splatting using Learned Priors
Sungwon Hwang, Min-Jung Kim, Taewoong Kang +2
Neural rendering-based urban scene reconstruction methods commonly rely on images collected from driving vehicles with cameras facing and moving forward. Although these methods can…
TCAN: Animating Human Images with Temporally Consistent Pose Guidance using Diffusion Models
Jeongho Kim, Min-Jung Kim, Junsoo Lee +1
Pose-driven human-image animation diffusion models have shown remarkable capabilities in realistic human video synthesis. Despite the promising results achieved by previous approac…
Adapting Pretrained ViTs with Convolution Injector for Visuo-Motor Control
Dongyoon Hwang, Byungkun Lee, Hojoon Lee +2
Vision Transformers (ViT), when paired with large-scale pretraining, have shown remarkable performance across various computer vision tasks, primarily due to their weak inductive b…
Regularized Training with Generated Datasets for Name-Only Transfer of Vision-Language Models
Minho Park, Sunghyun Park, Jooyeol Yun +1
Recent advancements in text-to-image generation have inspired researchers to generate datasets tailored for perception models using generative models, which prove particularly valu…