6 papers
Combined Flicker-banding and Moire Removal for Screen-Captured Images
Libo Zhu, Zihan Zhou, Zhiyi Zhou +5
Capturing display screens with mobile devices has become increasingly common, yet the resulting images often suffer from severe degradations caused by the coexistence of moiré patt…
RIFLE: Removal of Image Flicker-Banding via Latent Diffusion Enhancement
Libo Zhu, Zihan Zhou, Xiaoyang Liu +4
Capturing screens is now routine in our everyday lives. But the photographs of emissive displays are often influenced by the flicker-banding (FB), which is alternating bright%u2013…
QuantVSR: Low-Bit Post-Training Quantization for Real-World Video Super-Resolution
Bowen Chai, Zheng Chen, Libo Zhu +3
Diffusion models have shown superior performance in real-world video super-resolution (VSR). However, the slow processing speeds and heavy resource consumption of diffusion models…
QuantFace: Efficient Quantization for Face Restoration
Jiatong Li, Libo Zhu, Haotong Qin +5
Diffusion models have been achieving remarkable performance in face restoration. However, the heavy computations hamper the widespread adoption of these models. In this work, we pr…
QArtSR: Quantization via Reverse-Module and Timestep-Retraining in One-Step Diffusion based Image Super-Resolution
Libo Zhu, Haotong Qin, Kaicheng Yang +5
One-step diffusion-based image super-resolution (OSDSR) models are showing increasingly superior performance nowadays. However, although their denoising steps are reduced to one an…
PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution
Libo Zhu, Jianze Li, Haotong Qin +4
Diffusion-based image super-resolution (SR) models have shown superior performance at the cost of multiple denoising steps. However, even though the denoising step has been reduced…