Intrinsic images by clustering
… first find clusters of similar reflectance in the image following … boundaries between clusters
(as opposed to the whole image), … preserving reflectance between clusters even if they are not …
(as opposed to the whole image), … preserving reflectance between clusters even if they are not …
Recovering intrinsic images with a global sparsity prior on reflectance
… Every reflectance component ri belongs to one of the clusters and we denote its cluster
membership with the variable αi ∈ {1,...,C}. This is summarized in the following energy term …
membership with the variable αi ∈ {1,...,C}. This is summarized in the following energy term …
Towards uncovering the intrinsic data structures for unsupervised domain adaptation using structurally regularized deep clustering
… directly uncovers the intrinsic discrimination of target data via constrained clustering, where
we … Technically, we propose a hybrid model of deep clustering that integrates a regularized …
we … Technically, we propose a hybrid model of deep clustering that integrates a regularized …
Intrinsic mean shift for clustering on Stiefel and Grassmann manifolds
HE Cetingul, R Vidal�- 2009 IEEE Conference on Computer�…, 2009 - ieeexplore.ieee.org
… The maximum clustering rates are indicated in parenthesis. We observe that the clustering
rates of the intrinsic and extrinsic formulations are comparable but relatively lower than the …
rates of the intrinsic and extrinsic formulations are comparable but relatively lower than the …
Combining intrinsic dimension and local tangent space for manifold spectral clustering image segmentation
X Yao, R Zhang, J Hu, K Chang, X Liu, J Zhao�- Soft Computing, 2022 - Springer
… 3, theoretical basis of spectral clustering, intrinsic dimension and local tangent space are …
using intrinsic dimension and local tangent space, the manifold spectral clustering based on …
using intrinsic dimension and local tangent space, the manifold spectral clustering based on …
User-assisted intrinsic images
… We demonstrate intrinsic image decomposition on a variety of images and show … Figure 7:
For a downsampling factor p, we use K-means clustering to extract v2 representative colors of …
For a downsampling factor p, we use K-means clustering to extract v2 representative colors of …
Intrinsic classification of single particle images by spectral clustering
Y Ueno, M Kawata, S Umeyama�- The First International Workshop�…, 2005 - scitepress.org
… with simulated transmission electron microscope images and a data set from a … intrinsic
classification of images with a common motif. We also discuss a mechanism for clustering images …
classification of images with a common motif. We also discuss a mechanism for clustering images …
Deep adaptive image clustering
… also have some intrinsic limitations. First, multi-stage … the image clustering task as a binary
pairwise-classification problem to judge whether pairs of images belong to the same clusters. …
pairwise-classification problem to judge whether pairs of images belong to the same clusters. …
Intrinsic images
MF Tappen�- Computer Vision: A Reference Guide, 2021 - Springer
… so that lighting can be accounted for in image understanding. To simplify inference, methods
for … Most techniques perform this estimation on a single input image, as this allows for wider …
for … Most techniques perform this estimation on a single input image, as this allows for wider …
Image clustering using local discriminant models and global integration
In this paper, we propose a new image clustering algorithm, referred to as clustering using …
the clustering performance of samples within the local clique. To obtain the clustering result, …
the clustering performance of samples within the local clique. To obtain the clustering result, …
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