Non-local color compensation network for intrinsic image decomposition
Single image-based intrinsic image decomposition attempts to separate one input image
into several intrinsic components, which is inherently an under-constrained problem. Some …
into several intrinsic components, which is inherently an under-constrained problem. Some …
Intrinsic Appearance Decomposition Using Point Cloud Representation
X Xing, K Groh, S Karaoglu… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
The aim of intrinsic decomposition is to deduce the albedo and shading components,
typically from 2D images. However, this task is ill-posed, necessitating previous methods to …
typically from 2D images. However, this task is ill-posed, necessitating previous methods to …
Intrinsic omnidirectional image decomposition with illumination pre-extraction
Capturing an omnidirectional image with a 360-degree field of view entails capturing
intricate spatial and lighting details of the scene. Consequently, existing intrinsic image …
intricate spatial and lighting details of the scene. Consequently, existing intrinsic image …
Extraordinarily Time-and Memory-Efficient Large-Scale Canonical Correlation Analysis in Fourier Domain: From Shallow to Deep
XJ Shen, Z Xu, L Wang, Z Li, G Liu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Canonical correlation analysis (CCA) is a correlation analysis technique that is widely used
in statistics and the machine-learning community. However, the high complexity involved in …
in statistics and the machine-learning community. However, the high complexity involved in …
CRefNet: Learning Consistent Reflectance Estimation With a Decoder-Sharing Transformer
We present CRefNet, a hybrid transformer-convolutional deep neural network for consistent
reflectance estimation in intrinsic image decomposition. Estimating consistent reflectance is …
reflectance estimation in intrinsic image decomposition. Estimating consistent reflectance is …
Intrinsic Image Decomposition Based on Retinex Theory, Superpixel Segmentation and Scale-Space Computations
Intrinsic image decomposition enables us to estimate the low-level features of images. Due
to the benefits it provides and the challenges it holds, intrinsic image decomposition has …
to the benefits it provides and the challenges it holds, intrinsic image decomposition has …
Time and Memory Efficient Large-Scale Canonical Correlation Analysis in Fourier Domain
XJ Shen, Z Xu, L Wang, Z Li - Proceedings of the 30th ACM International …, 2022 - dl.acm.org
Canonical correlation analysis (CCA) is a linear correlation analysis technique used widely
in the statistics and machine learning community. However, the high complexity involved in …
in the statistics and machine learning community. However, the high complexity involved in …
Single Scene Image Editing Based on Deep Intrinsic Decomposition
H Sha, Y Liu, K Lu, C Lu, H Chen, Y Wang - Image and Graphics: 11th …, 2021 - Springer
Intrinsic decomposition is an inherent problem in computer graphics and computer vision,
which decomposes an image into a reflectance image and a shading image. Through the …
which decomposes an image into a reflectance image and a shading image. Through the …