7 papers
Bridging Restoration and Generation in One-step Diffusion for Real-World Image Super-Resolution
Shyang-En Weng, Yi-Cheng Liao, Yu-Syuan Xu +3
Pretrained diffusion models have revolutionized real-world image super-resolution (Real-ISR), but their iterative sampling is computationally prohibitive, driving efforts to distil…
Controllable Collision Scenario Generation via Collision Pattern Prediction
Pin-Lun Chen, Chi-Hsi Kung, Che-Han Chang +2
Evaluating the safety of autonomous vehicles (AVs) requires diverse, safety-critical scenarios, with collisions being especially important yet rare and unsafe to collect in the rea…
Learning Ordinal Degradation Representations with Textual Priors for Diffusion-Based Blind Image Super-Resolution
Yi-Cheng Liao, Shyang-En Weng, Yu-Syuan Xu +4
Blind image super-resolution (Blind SR) has achieved remarkable perceptual quality via generative priors. However, lacking clear degradation representations such as varying severit…
Two Heads Better than One: Dual Degradation Representation for Blind Super-Resolution
Hsuan Yuan, Shao-Yu Weng, I-Hsuan Lo +5
Previous methods have demonstrated remarkable performance in single image super-resolution (SISR) tasks with known and fixed degradation (e.g., bicubic downsampling). However, when…
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…
RC-AutoCalib: An End-to-End Radar-Camera Automatic Calibration Network
Van-Tin Luu, Yon-Lin Cai, Vu-Hoang Tran +3
This paper presents a groundbreaking approach - the first online automatic geometric calibration method for radar and camera systems. Given the significant data sparsity and measur…