Video Restoration

Ev-DeblurVSR can turn low-resolution and blurry videos into high-resolution ones.

VISION-XL can deblur and upscale videos using SDXL. It supports different aspect ratios and can produce HD videos in under 2.5 minutes on a single NVIDIA 4090 GPU, using only 13GB of VRAM for 25-frame videos.

SVFR can restore high-quality video faces from low-quality inputs. It combines video face restoration, inpainting, and colorization to improve the overall quality and coherence of the restored videos.

KEEP can enhance video face super-resolution by maintaining consistency across frames. It uses Kalman filtering to improve facial details, working well on both synthetic and real-world videos.

Noise Calibration can improve video quality while keeping the original content structure. It uses a noise optimization strategy with pre-trained diffusion models to enhance visuals and ensure consistency between original and enhanced videos.

ST-AVSR can enhance video resolution at any size while keeping details clear and smooth. It uses a pre-trained VGG network to improve quality and speed, making it better than other methods.

DiffIR2VR-Zero is a zero-shot video restoration method that can be used with any 2D image restoration diffusion model. The method is able to do 8x super-resolution and high-standard deviation video denoising.

EvTexture is a video super-resolution upscaling method that utilizes event signals for texture enhancement for more accurate texture and high-resolution detail recovery.

FMA-Net can turn blurry, low-quality videos into clear, high-quality ones by accurately predicting the degradation and restoration processes, considering the movement in the video through advanced learning of motion patterns.

Blind Video Deflickering by Neural Filtering with a Flawed Atlas can remove flicker from videos without needing extra guidance. It works well on different types of videos and uses a neural atlas for better consistency, outperforming other methods.