Search Results for author:
Found 10 papers, 5 papers with code
HardGAN: A Haze-Aware Representation Distillation GAN for Single Image Dehazing
In this paper, we present a Haze-Aware Representation Distillation Generative Adversarial Network named HardGAN for single-image dehazing.
Image Deraining via Self-supervised Reinforcement Learning
The work aims to recover rain images by removing rain streaks via Self-supervised Reinforcement Learning (RL) for image deraining (SRL-Derain).
ViStripformer: A Token-Efficient Transformer for Versatile Video Restoration
Besides, ViStripformer is an effective and efficient transformer architecture with much lower memory usage than the vanilla transformer.
ID-Blau: Image Deblurring by Implicit Diffusion-based reBLurring AUgmentation
We parameterize the blur patterns of a blurred image with their orientations and magnitudes as a pixel-wise blur condition map to simulate motion trajectories and implicitly represent them in a continuous space.
Meta Transferring for Deblurring
Most previous deblurring methods were built with a generic model trained on blurred images and their sharp counterparts.
Stripformer: Strip Transformer for Fast Image Deblurring
Images taken in dynamic scenes may contain unwanted motion blur, which significantly degrades visual quality.
Ranked #2 on
Deblurring
on RealBlur-R
BANet: Blur-aware Attention Networks for Dynamic Scene Deblurring
Image motion blur results from a combination of object motions and camera shakes, and such blurring effect is generally directional and non-uniform.
Ranked #5 on
Deblurring
on RealBlur-R
Weakly Supervised Instance Segmentation using the Bounding Box Tightness Prior
This paper presents a weakly supervised instance segmentation method that consumes training data with tight bounding box annotations.
Box-supervised Instance Segmentation
Multiple Instance Learning
+4
DotSCN: Group Re-identification via Domain-Transferred Single and Couple Representation Learning
To gain the superiority of deep learning models, we treat a group as multiple persons and transfer the domain of a labeled ReID dataset to a G-ReID target dataset style to learn single representations.
Unsupervised CNN-based Co-Saliency Detection with Graphical Optimization
In this paper, we address co-saliency detection in a set of images jointly covering objects of a specific class by an unsupervised convolutional neural network (CNN).
