highlight removal

10 papers with code • 0 benchmarks • 0 datasets

Highlight removal refers to the process of eliminating or reducing the presence of specular highlights in an image. Specular highlights are bright spots or reflections that occur when light reflects off a shiny or reflective surface, such as glass, metal, or oily skin. These highlights can often obscure or distort the underlying details of the image, making it difficult to analyze or process.

Most implemented papers

Single Image Highlight Removal with a Sparse and Low-Rank Reflection Model

dingguanglei/SLRR-SparseAndLowRankReflectionModel ECCV 2018

We propose a sparse and low-rank reflection model for specular highlight detection and removal using a single input image.

Polarization Guided Specular Reflection Separation

wsj890411/Polar_HR 22 Mar 2021

Based on the analysis of polarization, we propose a polarization guided model to generate a polarization chromaticity image, which is able to reveal the geometrical profile of the input image in complex scenarios, such as diversity of illumination.

A Multi-Task Network for Joint Specular Highlight Detection and Removal

fu123456/SHIQ CVPR 2021

Specular highlight detection and removal are fundamental and challenging tasks.

Text-Aware Single Image Specular Highlight Removal

weizequan/tashr PRCV 2021

The core goal is to improve the accuracy of text detection and recognition by removing the highlight from text images.

Single-Image Specular Highlight Removal via Real-World Dataset Construction

jianweiguo/SpecularityNet-PSD TMM 2021

Specular reflections pose great challenges on various multimedia and computer vision tasks, e. g. , image segmentation, detection and matching.

M2-Net: Multi-stages Specular Highlight Detection and Removal in Multi-scenes

kjzju/specular-removal 20 Jul 2022

The framework consists of three main components, highlight feature extractor module, highlight coarse removal module, and highlight refine removal module.

Estimating Reflectance Layer from A Single Image: Integrating Reflectance Guidance and Shadow/Specular Aware Learning

jinyeying/S-Aware-network 27 Nov 2022

To further enforce the reflectance layer to be independent of shadows and specularities in the second-stage refinement, we introduce an S-Aware network that distinguishes the reflectance image from the input image.

Joint network for specular highlight detection and adversarial generation of specular-free images trained with polarimetric data

Atif-Anwer/SHMGAN Neurocomputing 2023

Once trained, SHMGAN is able to generate specular-free images from a single RGB image as input; without requiring any additional external labels.

Dual-Hybrid Attention Network for Specular Highlight Removal

CXH-Research/DHAN-SHR 17 Jul 2024

Specular highlight removal plays a pivotal role in multimedia applications, as it enhances the quality and interpretability of images and videos, ultimately improving the performance of downstream tasks such as content-based retrieval, object recognition, and scene understanding.