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20242026
most citedQArtSR: Quantization via Reverse-Module and Timestep-Retraining in One-Step Diffusion based Image Super-Resolution

1 citations · 1 across the 11 of their papers we have counts for

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cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

Freqformer: Image-Demoiréing Transformer via Effective Frequency Decomposition

Xiaoyang Liu, Bolin Qiu, Zheng Chen +5

Image demoiréing remains a challenging task due to the complex interplay between texture corruption and color distortions caused by moiré patterns. Existing methods, especially tho…

cs.CV2025★ 1 cited

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…