10 papers
From Prompt to Progression: Taming Video Diffusion Models for Seamless Attribute Transition
Ling Lo, Kelvin C. K. Chan, Wen-Huang Cheng +1
Existing models often struggle with complex temporal changes, particularly when generating videos with gradual attribute transitions. The most common prompt interpolation approach…
HoliGS: Holistic Gaussian Splatting for Embodied View Synthesis
Xiaoyuan Wang, Yizhou Zhao, Botao Ye +6
We propose HoliGS, a novel deformable Gaussian splatting framework that addresses embodied view synthesis from long monocular RGB videos. Unlike prior 4D Gaussian splatting and dyn…
CoCoIns: Consistent Subject Generation via Contrastive Instantiated Concepts
Lee Hsin-Ying, Kelvin C. K. Chan, Ming-Hsuan Yang
While text-to-image generative models can synthesize diverse and faithful content, subject variation across multiple generations limits their application to long-form content gener…
HoliSDiP: Image Super-Resolution via Holistic Semantics and Diffusion Prior
Li-Yuan Tsao, Hao-Wei Chen, Hao-Wei Chung +4
Text-to-image diffusion models have emerged as powerful priors for real-world image super-resolution (Real-ISR). However, existing methods may produce unintended results due to noi…
KITTEN: A Knowledge-Intensive Evaluation of Image Generation on Visual Entities
Hsin-Ping Huang, Xinyi Wang, Yonatan Bitton +8
Recent advances in text-to-image generation have improved the quality of synthesized images, but evaluations mainly focus on aesthetics or alignment with text prompts. Thus, it rem…
A Simple Approach to Unifying Diffusion-based Conditional Generation
Xirui Li, Charles Herrmann, Kelvin C. K. Chan +4
Recent progress in image generation has sparked research into controlling these models through condition signals, with various methods addressing specific challenges in conditional…
Re-boosting Self-Collaboration Parallel Prompt GAN for Unsupervised Image Restoration
Xin Lin, Yuyan Zhou, Jingtong Yue +4
Unsupervised restoration approaches based on generative adversarial networks (GANs) offer a promising solution without requiring paired datasets. Yet, these GAN-based approaches st…
AdaIR: Exploiting Underlying Similarities of Image Restoration Tasks with Adapters
Hao-Wei Chen, Yu-Syuan Xu, Kelvin C. K. Chan +3
Existing image restoration approaches typically employ extensive networks specifically trained for designated degradations. Despite being effective, such methods inevitably entail…
Effective Adapter for Face Recognition in the Wild
Yunhao Liu, Yu-Ju Tsai, Kelvin C. K. Chan +3
In this paper, we tackle the challenge of face recognition in the wild, where images often suffer from low quality and real-world distortions. Traditional heuristic approaches-eith…
Multi-task Image Restoration Guided By Robust DINO Features
Xin Lin, Jingtong Yue, Kelvin C. K. Chan +4
Multi-task image restoration has gained significant interest due to its inherent versatility and efficiency compared to its single-task counterpart. However, performance decline is…