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Found 15 papers, 5 papers with code
Learning to See in the Dark with Events
A detail enhancing branch is proposed to reconstruct day light-specific features from the domain-invariant representations in a residual manner, regularized by a ranking loss.
Learning Event-Driven Video Deblurring and Interpolation
Event-based sensors, which have a response if the change of pixel intensity exceeds a triggering threshold, can capture high-speed motion with microsecond accuracy.
Diffusion-based Blind Text Image Super-Resolution
Since text prior is important to guarantee the correctness of the restored text structure according to existing arts, we also propose a Text Diffusion Model (TDM) for text recognition which can guide IDM to generate text images with correct structures.
Predicting Scores of Various Aesthetic Attribute Sets by Learning from Overall Score Labels
Then, we define an aesthetic attribute contribution to describe the role of aesthetic attributes throughout an image and use it with the attribute scores and the overall scores to train our F2S model.
Range-Nullspace Video Frame Interpolation With Focalized Motion Estimation
Continuous-time video frame interpolation is a fundamental technique in computer vision for its flexibility in synthesizing motion trajectories and novel video frames at arbitrary intermediate time steps.
Focusing on Persons: Colorizing Old Images Learning from Modern Historical Movies
Classification sub-module supplies classifying of images according to the eras, nationalities and garment types; Parsing sub-network supplies the semantic for person contours, clothing and background in the image to achieve more accurate colorization of clothes and persons and prevent color overflow.
Bringing Events Into Video Deblurring With Non-Consecutively Blurry Frames
EFM can also be easily incorporated into existing deblurring networks, making event-driven deblurring task benefit from state-of-the-art deblurring methods.
Training Weakly Supervised Video Frame Interpolation With Events
Though trained on low frame-rate videos, our framework outperforms existing models trained with full high frame-rate videos (and events) on both GoPro dataset and a new real event-based dataset.
Learning Event-Based Motion Deblurring
Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process.
Ranked #27 on
Image Deblurring
on GoPro
(using extra training data)
Aesthetic Attributes Assessment of Images
This is a new formula of image aesthetic assessment, which predicts aesthetic attributes captions together with the aesthetic score of each attribute.
Video Matting via Sparse and Low-Rank Representation
We introduce a novel method of video matting via sparse and low-rank representation.
Conformal and Low-Rank Sparse Representation for Image Restoration
In this paper, we propose a novel sparse representation approach called conformal and low-rank sparse representation (CLRSR) for image restoration problems.
Sparse Dictionary Learning for Edit Propagation of High-Resolution Images
Previous approaches for edit propagation typically employ a global optimization over the whole set of image pixels, incurring a prohibitively high memory and time consumption for high-resolution images.
Image Matting with Local and Nonlocal Smooth Priors
This nonlocal smooth prior and the well known local smooth prior from matting Laplacian complement each other.
