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Pascal3D and ShapeNet
The dataset used in the paper for object detection, self-driving, and UAV racing tasks. -
CIFAR-100 and ImageNet datasets
The dataset used in the paper is the CIFAR-100 and ImageNet datasets. -
Vision-and-Language Navigation
The Vision-and-Language Navigation (VLN) task gives a global natural sentence I = {w0,..., wl} as an instruction, where wi is a word token while the l is the length of the... -
Waymo Open Dataset and nuScenes Dataset
The Waymo Open Dataset and the nuScenes Dataset are used to evaluate the performance of the AFDetV2 model. -
Symmetric parallax attention for stereo image super-resolution
Symmetric parallax attention for stereo image super-resolution. -
Learning parallax attention for stereo image super-resolution
Learning parallax attention for stereo image super-resolution. -
Feedback network for mutually boosted stereo image super-resolution and dispa...
Stereo image super-resolution aims at enhancing the quality of super-resolution results by utilizing the complementary information provided by binocular systems. -
NAFSSR: Stereo Image Super-Resolution Using NAFNet
Stereo image super-resolution aims at enhancing the quality of super-resolution results by utilizing the complementary information provided by binocular systems. -
Animal Kingdom
A large and diverse dataset for animal behavior understanding. -
Hierarchical 3D fully convolutional networks for multi-organ segmentation
A two-stage, coarse-to-fine approach that trains an FCN model to roughly delineate the organs of interest in the first stage and then uses these predictions of the first-stage... -
X-volution: On the Unification of Convolution and Self-attention
Convolution and self-attention are acting as two fundamental building blocks in deep neural networks, where the former extracts local image features in a linear way while the... -
ConvMLP: Hierarchical Convolutional MLPs for Vision
ConvMLP: a Hierarchical Convolutional MLP backbone for visual recognition -
MNIST and FashionMNIST
The MNIST and FashionMNIST datasets are used to test the performance of the proposed generative autoencoders. -
FMoW-WILDS
Functional map of the world. -
LiqD: A Dynamic Liquid Level Detection Model
A container dynamic liquid level detection model based on U²-Net. -
WeakTr: Exploring Plain Vision Transformer for Weakly-supervised Semantic Seg...
Weakly-supervised semantic segmentation using plain Vision Transformer (ViT) for Weakly-supervised Semantic Segmentation (WSSS). -
Cloud-removal-from-solar-imagery
The dataset used for removing cloud shadows from ground-based solar imagery. -
Classification of Diabetic Retinopathy using Pre-Trained Deep Learning Models
Diabetic Retinopathy dataset containing 1000 color fundus images from KAGGLE
