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DiffVQA: Video Quality Assessment Using Diffusion Feature Extractor
Wei-Ting Chen, Yu-Jiet Vong, Yi-Tsung Lee +4
Video Quality Assessment (VQA) aims to evaluate video quality based on perceptual distortions and human preferences. Despite the promising performance of existing methods using Con…
InstantRestore: Single-Step Personalized Face Restoration with Shared-Image Attention
Howard Zhang, Yuval Alaluf, Sizhuo Ma +3
Face image restoration aims to enhance degraded facial images while addressing challenges such as diverse degradation types, real-time processing demands, and, most crucially, the…
Delving Deep into Engagement Prediction of Short Videos
Dasong Li, Wenjie Li, Baili Lu +4
Understanding and modeling the popularity of User Generated Content (UGC) short videos on social media platforms presents a critical challenge with broad implications for content c…
RobustSAM: Segment Anything Robustly on Degraded Images
Wei-Ting Chen, Yu-Jiet Vong, Sy-Yen Kuo +2
Segment Anything Model (SAM) has emerged as a transformative approach in image segmentation, acclaimed for its robust zero-shot segmentation capabilities and flexible prompting sys…
DSL-FIQA: Assessing Facial Image Quality via Dual-Set Degradation Learning and Landmark-Guided Transformer
Wei-Ting Chen, Gurunandan Krishnan, Qiang Gao +3
Generic Face Image Quality Assessment (GFIQA) evaluates the perceptual quality of facial images, which is crucial in improving image restoration algorithms and selecting high-quali…
Personalized Restoration via Dual-Pivot Tuning
Pradyumna Chari, Sizhuo Ma, Daniil Ostashev +4
Generative diffusion models can serve as a prior which ensures that solutions of image restoration systems adhere to the manifold of natural images. However, for restoring facial i…