43 datasets found

Crowd counting has drawn increasing attention because of its fundamental role in social management. Six datasets are used in our experiments, i.e., GCC, ShanghaiTech PartA,...

Real-world domain adaptation dataset for spam detection, which was released as part of the ECML PKDD 2006 Discovery Challenge.

Synthetic regression problem with two users attempting to fit a linear model of the function f (x1, x2) = 5x1 − 2x2 + 0.5x3^2. Each user has input data drawn from a distinct...

A semi-supervised active domain adaptation framework for semantic segmentation in driving scenes.

The dataset used for extensive cut-and-paste augmentation for unsupervised domain adaptive semantic segmentation.

The dataset used for unsupervised domain adaptation for semantic segmentation with pseudo label self-refinement.

The dataset used for sim-to-real domain adaptation in robotics, consisting of tasks with randomized dynamics.

The dataset used in this paper for unsupervised domain adaptation.

Select-by-Distinctive-Margin (SDM) is a simple yet effective active learning method for active domain adaptation.

The Office-31 dataset is a benchmark dataset for domain adaptation, containing images from the Amazon domain.

The Office+Caltech-10 dataset is a benchmark dataset for domain adaptation, combining Office-10 and Caltech-10 datasets.

The proposed method is implemented by the Pytorch framework using a NVIDIA GeForce RTX 3090 GPU with 24GB memory.

The PointDA-10 dataset consists of three subsets of three widely-used datasets: ShapeNet, ModelNet, and ScanNet. All three subsets share the same ten distinct classes.

A dataset for the study of domain adaptation solutions, composed of synthetic and real videos from seven gesture classes, from both the ground and air perspectives.

The Hyper-Kvasir→Piccolo task is a domain adaptation task for semantic segmentation, where the source domain is Hyper-Kvasir and the target domain is Piccolo.

The Synthia→Cityscapes task is a domain adaptation task for semantic segmentation, where the source domain is Synthia and the target domain is Cityscapes.

The Office-Home dataset is a visual domain adaptation task, where the goal is to adapt a model trained in a source domain to a target domain with different distributions.

The dataset used for out-of-distribution segmentation, zero-shot semantic segmentation, and domain adaptation.

Biwi Kinect is a real-world dataset containing over 15K images of 20 people.

MPI3D is a benchmark dataset that consists of 1,036,800 examples of 3D objects from three different domains: Toy, RealisticC, and Real.