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ImageNet Large Scale Visual Recognition Challenge (ILSVRC)
The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) dataset is a large-scale image classification dataset containing over 14 million images from 21,841 categories. -
CIFAR-10, CIFAR-100, and Tiny-ImageNet datasets
The CIFAR-10, CIFAR-100, and Tiny-ImageNet datasets used for training and testing the proposed framework. -
Image Inpainting
The CelebAHQ dataset was used with a fixed removal mask located near the image centers [11]. -
MegaDepth dataset
The dataset used for training the D2-Net model, consisting of 327,036 image pairs with at least 50% overlap in the sparse SfM point cloud. -
ALIKED: A Lighter Keypoint and Descriptor Extraction Network via Deformable T...
The proposed method incorporates a deformable transformation into the descriptors, making them more robust. The SDDH extracts descriptors only on sparse keypoints, which... -
Acne Assessment from Selfie Images
Acne severity assessment from selfie images using deep learning model -
ETH3D Benchmark
The ETH3D Benchmark dataset contains a set of objects 3D coordinates, images in which these objects can be seen, the intrinsic parameters and the pose of each of the cameras... -
ArtFusion: Controllable Arbitrary Style Transfer using Dual Conditional Laten...
Arbitrary Style Transfer (AST) aims to transform images by adopting the style from any selected artwork. Nonethe-less, the need to accommodate diverse and subjective user... -
PACS dataset
The dataset used in the paper is a large collection of small images, each representing a patch of a jigsaw puzzle. The patches are of the same size and orientation, and the goal... -
HTC-DC Net
The proposed network utilizes a classification-regression paradigm with a ViT to incorporate holistic features and local features. The regression phase with hybrid regression... -
A novel approach for multi-label chest X-ray classification of common thorax ...
A novel approach for multi-label chest X-ray classification of common thorax diseases. -
MPI3D dataset
The dataset used in the paper is a MPI3D dataset, which contains 3D images of objects with varying sizes and colors. -
Shapes3D dataset
The dataset used in the paper is a Shapes3D dataset, which contains 3D shapes with varying sizes and colors. -
Mitosis domain generalization challenge
The MIDOG Challenge was a competition on mitosis detection held at the International Conference on Medical Image Computing and Computer Assisted Intervention, 2021. -
Lidar panoptic segmentation for autonomous driving
Lidar panoptic segmentation for autonomous driving -
Inria Aerial Image Labeling dataset
Inria Aerial Image Labeling dataset contains aerial orthorectified color imagery of 5000 × 5000 pixels with a spatial resolution of 0.3 m.
