From the 1 of 6 linked papers with an AI index.
6 papers
FreeLit: Paired-Free Indoor Relighting via Physics-Guided Diffusion
Chi-En Yen, Duy-Khanh Ngo, Wen-Wei Tang +3
FreeLit introduces a paired‑free indoor relighting method that uses physics‑guided illumination priors and a diffusion model to let users control light position, color, and intensi…
IDAG-Edit: Multi-Object Video Editing via Instance-Decoupled Attention and Guidance
Yuan-Zhih Lin, Huu-Thang Nguyen, Huu-Phu Do +2
Diffusion-based video editing has made significant progress; however, achieving precise and temporally consistent object-level control, especially in multi-object scenarios, remain…
ExReg: Wide-range Photo Exposure Correction via a Multi-dimensional Regressor with Attention
Huu-Phu Do, Hao-Chien Hsueh, Tzu-Hao Chiang +3
Photo exposure correction is widely investigated, but fewer studies focus on correcting under- and over-exposed images simultaneously. Three issues remain open to handle and correc…
DynFaceRestore: Balancing Fidelity and Quality in Diffusion-Guided Blind Face Restoration with Dynamic Blur-Level Mapping and Guidance
Huu-Phu Do, Yu-Wei Chen, Yi-Cheng Liao +4
Blind Face Restoration aims to recover high-fidelity, detail-rich facial images from unknown degraded inputs, presenting significant challenges in preserving both identity and deta…
TimeNeRF: Building Generalizable Neural Radiance Fields across Time from Few-Shot Input Views
Hsiang-Hui Hung, Huu-Phu Do, Yung-Hui Li +1
We present TimeNeRF, a generalizable neural rendering approach for rendering novel views at arbitrary viewpoints and at arbitrary times, even with few input views. For real-world a…
Blind Super Resolution with Reference Images and Implicit Degradation Representation
Huu-Phu Do, Po-Chih Hu, Hao-Chien Hsueh +3
Previous studies in blind super-resolution (BSR) have primarily concentrated on estimating degradation kernels directly from low-resolution (LR) inputs to enhance super-resolution.…