Search Results for author:
Found 11 papers, 10 papers with code
Deterministic Neural Illumination Mapping for Efficient Auto-White Balance Correction
Our method provides an efficient deep learning-based AWB correction solution, promising real-time, high-quality color correction for digital imaging applications.
Reversed Image Signal Processing and RAW Reconstruction. AIM 2022 Challenge Report
Cameras capture sensor RAW images and transform them into pleasant RGB images, suitable for the human eyes, using their integrated Image Signal Processor (ISP).
AIM 2022 Challenge on Instagram Filter Removal: Methods and Results
This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal.
Reversing Image Signal Processors by Reverse Style Transferring
Mapping from sRGB to RAW format could be a relevant domain for reverse style transferring since the task is an ill-posed reversing problem.
Modeling the Lighting in Scenes as Style for Auto White-Balance Correction
Style may refer to different concepts (e. g. painting style, hairstyle, texture, color, filter, etc.)
Patch-wise Contrastive Style Learning for Instagram Filter Removal
Assuming these filters substantially inject a piece of additional style information to the social media images, we can formulate the problem of recovering the original versions as a reverse style transfer problem.
Instagram Filter Removal on Fashionable Images
However, CNNs generally fail to interpret both the image and its filtered version as the same in the visual analysis of social media images.
[Re] Spatial-Adaptive Network for Single Image Denoising
The original paper proposes an encoder-decoder structure exploiting a residual spatialadaptive block and a context block to capture multi-scale information for achieving the state-of-the-art on real and synthetic noise removal.
A Benchmark for Inpainting of Clothing Images with Irregular Holes
\keywords{image inpainting, fashion image understanding, dilated convolutions, partial convolutions
Quaternion Capsule Networks
Capsules are grouping of neurons that allow to represent sophisticated information of a visual entity such as pose and features.
Fashion Image Retrieval with Capsule Networks
In this study, we investigate in-shop clothing retrieval performance of densely-connected Capsule Networks with dynamic routing.
Ranked #1 on
Image Retrieval
on DeepFashion
