18 papers · 1 filter
CA-LoRA: Concept-Aware LoRA for Domain-Aligned Segmentation Dataset Generation
Minho Park, Sunghyun Park, Jungsoo Lee +5
This paper addresses the challenge of data scarcity in semantic segmentation by generating datasets through text-to-image (T2I) generation models, reducing image acquisition and la…
PromptDresser: Improving the Quality and Controllability of Virtual Try-On via Generative Textual Prompt and Prompt-aware Mask
Jeongho Kim, Hoiyeong Jin, Sunghyun Park +1
Recent virtual try-on approaches have advanced by finetuning pre-trained text-to-image diffusion models to leverage their powerful generative ability. However, the use of text prom…
TV-LiVE: Training-Free, Text-Guided Video Editing via Layer Informed Vitality Exploitation
Min-Jung Kim, Dongjin Kim, Seokju Yun +1
Video editing has garnered increasing attention alongside the rapid progress of diffusion-based video generation models. As part of these advancements, there is a growing demand fo…
Zero-Shot Head Swapping in Real-World Scenarios
Taewoong Kang, Sohyun Jeong, Hyojin Jang +1
With growing demand in media and social networks for personalized images, the need for advanced head-swapping techniques, integrating an entire head from the head image with the bo…
GaussianMotion: End-to-End Learning of Animatable Gaussian Avatars with Pose Guidance from Text
Gyumin Shim, Sangmin Lee, Jaegul Choo
In this paper, we introduce GaussianMotion, a novel human rendering model that generates fully animatable scenes aligned with textual descriptions using Gaussian Splatting. Althoug…
Enabling Region-Specific Control via Lassos in Point-Based Colorization
Sanghyeon Lee, Jooyeol Yun, Jaegul Choo
Point-based interactive colorization techniques allow users to effortlessly colorize grayscale images using user-provided color hints. However, point-based methods often face chall…