6 papers
PixelSR: Efficient Screen Content Super-Resolution via Pixel Classification
Zhiheng Li, Lei Chen, Jie Zhou +1
Screen content images are generally composed of texts and graphics. Compared to natural images, these man-made images contain a large quantity of sharp but repetitive structures. H…
UniGenDet: A Unified Generative-Discriminative Framework for Co-Evolutionary Image Generation and Generated Image Detection
Yanran Zhang, Wenzhao Zheng, Yifei Li +5
In recent years, significant progress has been made in both image generation and generated image detection. Despite their rapid, yet largely independent, development, these two fie…
VARestorer: One-Step VAR Distillation for Real-World Image Super-Resolution
Yixuan Zhu, Shilin Ma, Haolin Wang +6
Recent advancements in visual autoregressive models (VAR) have demonstrated their effectiveness in image generation, highlighting their potential for real-world image super-resolut…
More Than Sum of Its Parts: Deciphering Intent Shifts in Multimodal Hate Speech Detection
Runze Sun, Yu Zheng, Zexuan Xiong +4
Combating hate speech on social media is critical for securing cyberspace, yet relies heavily on the efficacy of automated detection systems. As content formats evolve, hate speech…
FADE: Frequency-Aware Diffusion Model Factorization for Video Editing
Yixuan Zhu, Haolin Wang, Shilin Ma +4
Recent advancements in diffusion frameworks have significantly enhanced video editing, achieving high fidelity and strong alignment with textual prompts. However, conventional appr…
InstaRevive: One-Step Image Enhancement via Dynamic Score Matching
Yixuan Zhu, Haolin Wang, Ao Li +6
Image enhancement finds wide-ranging applications in real-world scenarios due to complex environments and the inherent limitations of imaging devices. Recent diffusion-based method…