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Found 17 papers, 13 papers with code
Rolling Shutter Correction with Intermediate Distortion Flow Estimation
Additionally, a multi-distortion flow prediction strategy is integrated to mitigate the issue of inaccurate flow estimation further.
Taming Lookup Tables for Efficient Image Retouching
Existing enhancement models often optimize for high performance while falling short of reducing hardware inference time and power consumption, especially on edge devices with constrained computing and storage resources.
PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding
Recent advances in text-to-image generation have made remarkable progress in synthesizing realistic human photos conditioned on given text prompts.
Ranked #6 on
Diffusion Personalization Tuning Free
on AgeDB
Diffusion Personalization Tuning Free
Text-to-Image Generation
CustomNet: Zero-shot Object Customization with Variable-Viewpoints in Text-to-Image Diffusion Models
As a result, our CustomNet ensures enhanced identity preservation and generates diverse, harmonious outputs.
MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing
Despite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results.
Ranked #11 on
Text-based Image Editing
on PIE-Bench
OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer
Omnidirectional images (ODIs) have obtained lots of research interest for immersive experiences.
Polarized Color Image Denoising
Single-chip polarized color photography provides both visual textures and object surface information in one snapshot.
Blur Interpolation Transformer for Real-World Motion from Blur
This paper studies the challenging problem of recovering motion from blur, also known as joint deblurring and interpolation or blur temporal super-resolution.
Towards Real-World Video Deblurring by Exploring Blur Formation Process
We believe the novel realistic synthesis pipeline and the corresponding RAW video dataset can help the community to easily construct customized blur datasets to improve real-world video deblurring performance largely, instead of laboriously collecting real data pairs.
Learning Adaptive Warping for Real-World Rolling Shutter Correction
This paper proposes the first real-world rolling shutter (RS) correction dataset, BS-RSC, and a corresponding model to correct the RS frames in a distorted video.
MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment
No-Reference Image Quality Assessment (NR-IQA) aims to assess the perceptual quality of images in accordance with human subjective perception.
Ranked #8 on
Video Quality Assessment
on MSU SR-QA Dataset
VDTR: Video Deblurring with Transformer
For multi-frame temporal modeling, we adapt Transformer to fuse multiple spatial features efficiently.
Bringing Rolling Shutter Images Alive with Dual Reversed Distortion
In this paper, instead of two consecutive frames, we propose to exploit a pair of images captured by dual RS cameras with reversed RS directions for this highly challenging task.
StyleHEAT: One-Shot High-Resolution Editable Talking Face Generation via Pre-trained StyleGAN
Our framework elevates the resolution of the synthesized talking face to 1024*1024 for the first time, even though the training dataset has a lower resolution.
Accelerating Neural Network Optimization Through an Automated Control Theory Lens
We conduct experiments both from a control theory lens through a phase locus verification and from a network training lens on several models, including CNNs, Transformers, MLPs, and on benchmark datasets.
NTIRE 2021 Challenge on Perceptual Image Quality Assessment
This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021.
Region-Adaptive Deformable Network for Image Quality Assessment
Image quality assessment (IQA) aims to assess the perceptual quality of images.
