9 datasets found

Human parsing has recently attracted a huge amount of interests and achieved great progress with the advance of deep convolutional neural networks and large-scale datasets. Most...

The Look-into-Person (LIP) dataset is a dataset for human parsing and contains images of single persons with varying clothing appearances and diverse viewpoints.

The Fashionista dataset is a dataset for human parsing and contains images of single persons with upright position.

The Multiple Human Parsing (MHP) dataset is a large-scale dataset for multi-human parsing in the wild. It contains multiple persons captured in real-world scenes with...

The Gait3D-Parsing dataset is a large-scale parsing-based gait recognition dataset in the wild. It is an extension of the Gait3D dataset, which is collected from an in-the-wild...

The PASCAL-Context dataset comprises 4,998 images for training and 5,105 images for testing. This dataset offers dense labels for four tasks including semantic segmentation,...

Human parsing aims to segment a human image into multiple semantic parts. It is a pixel-level prediction task which requires to understand human images in both the global level...

Human parsing aims to segment a human image into multiple semantic parts. It is a pixel-level prediction task which requires to understand human images in both the global level...

Human parsing aims to segment a human image into multiple semantic parts. It is a pixel-level prediction task which requires to understand human images in both the global level...