Image Clustering
Image clustering is an important task in the field of computer vision, aiming to divide a dataset of images into semantically meaningful clusters without accessing ground truth labels. This task automatically discovers the inherent structure and patterns within images through unsupervised learning methods, thereby enabling effective organization and management of unlabeled images. Image clustering holds significant value in applications such as image retrieval, data mining, and content analysis.
ARL Polarimetric Thermal Face Dataset
Birdsnap
Caltech-101
CARS196
CIFAR-10
TEMI CLIP ViT-L (openai)
CIFAR-100
SPICE*
CIFAR-20
CLEVR Counts
CMU-PIE
coil-100
A-DSSC (Scattered)
Coil-20
JULE-RC
coil-40
A-DSSC (Scattered)
Country211
CUB-200-2011
CUB Birds
FineGAN
DTD
TURTLE (CLIP + DINOv2)
EMNIST-Balanced
AE+SNNL
EuroSAT
Extended Yale-B
DMSC
Fashion-MNIST
PRCut (DinoV2)
FER2013
FGVC Aircraft
Flowers-102
Food-101
FRGC
DEPICT
GTSRB
HAR
FCMI
Hateful Memes
ImageNet
TURTLE (CLIP + DINOv2)
ImageNet-10
DCCM
ImageNet-100
imagenet-1k
TAC
ImageNet-200
TEMI CLIP ViT-L (openai)
ImageNet-50
Imagenet-dog-15
MAE-CT (best)
Kinetics-700
KITTI
LetterA-J
DDC-DA
MNIST
MNIST-full
SPC
MNIST-test
DynAE
Oxford-IIIT Pets
PCam
pendigits
N2D (UMAP)
Rendered SST2
TURTLE (CLIP + DINOv2)
RESISC45
Stanford Cars
FineGAN
Stanford Dogs
FineGAN
STL-10
SPICE*
SUN397
Tiny-ImageNet
PRO-DSC
UCF101
UMist
J-DSSC (Scattered)
USPS
SPC
YouTube Faces DB
JULE-RC