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FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation
A Full Flow Bidirectional Fusion Network for 6D Pose Estimation from a single RGBD image -
Patient Data
A dataset of patient data for evaluating the performance of the proposed method. -
Phantom Data
The dataset is used to test the performance of the machine learning model for strain estimation and frame selection in ultrasound elastography. -
AAA Dataset
A dataset of pre-operative 3D CT scans and corresponding intra-operative 2D fluoroscopic images of AAA. -
Multi-label Transformer
The proposed Multi-label Transformer architecture is designed for multi-label image classification, combining pixel attention and cross-window attention to better excavate the... -
Dog StyleGAN2-ADA
Progress in GANs has enabled the generation of high-res-olution photorealistic images of astonishing quality. StyleGANs allow for compelling attribute modification on such... -
AnimalFace StyleGAN2-ADA
Progress in GANs has enabled the generation of high-res-olution photorealistic images of astonishing quality. StyleGANs allow for compelling attribute modification on such... -
ImageNet-R/A/Sk
The dataset used in the paper is not explicitly mentioned, but it is implied to be ImageNet-R/A/Sk for ImageNet-R/A/Sk classification. -
ImageNet-C/C
The dataset used in the paper is not explicitly mentioned, but it is implied to be ImageNet-C/C for ImageNet-C/C classification. -
ImageNet-50/100/200
The dataset used in the paper is not explicitly mentioned, but it is implied to be ImageNet-50/100/200 for ImageNet-50/100/200 classification. -
Occluded CIFAR
The dataset used in the paper is Occluded CIFAR. -
Cluttered MNIST and CIFAR-10
The dataset used in the paper is Cluttered MNIST and CIFAR-10. -
Counting Objects by Diffused Index
Counting objects is a fundamental but challenging problem. In this paper, we propose diffusion-based, geometry-free, and learning-free methodologies to count the number of... -
ImageNet-32
The ImageNet-32 dataset is a subset of the ImageNet dataset, containing 1,281,167 training samples and 50,000 test samples, distributed across 1,000 labels. -
DTU MVS Dataset
The DTU MVS dataset contains 49 images of physical objects in real environments. -
CIFAR10 and ImageNet
The dataset used in the paper to evaluate the alignment of deep neural networks with human perception. -
Fishyscapes
Fishyscapes: A benchmark for safe semantic segmentation in autonomous driving with annotations for pedestrian and vehicle detection. -
MUAD: Multiple Uncertainties for Autonomous Driving
MUAD: A synthetic dataset for autonomous driving with multiple uncertainties and annotations for semantic segmentation, depth estimation, object detection, and instance... -
Container: A General-Purpose Building Block for Multi-Head Context Aggregation
Convolutional neural networks (CNNs) are ubiquitous in computer vision, with a myriad of effective and efficient variations. Recently, Transformers – originally introduced in...
