HBW Dataset Papers With Code

Human Bodies in the Wild (HBW) is a validation and test set for body shape estimation. It consists of images taken in the wild and ground truth 3D body scans in SMPL-X topology. To create HBW, we collect body scans of 35 participants and register the SMPL-X model to the scans. Further each participant is photographed in various outfits and poses in front of a white background and uploads full-body photos of themselves taken in the wild. The validation and test set images are released. The ground truth shape is only released for the validation set.

VIP: A SIMD vectorized analytical query engine

kallisto_paper_analysis/simulations/analysis/R/NA12716_7_rsem.html at nbt · pachterlab/kallisto_paper_analysis · GitHub

Researchers From ETH Zurich And Microsoft Propose X-Avatar:, 41% OFF

Impaired local intrinsic immunity to SARS-CoV-2 infection in severe COVID-19 - ScienceDirect

From Codabar to ISBT 128: Implementing Barcode Technology in Blood BankAutomation System

MVPAlab: A machine learning decoding toolbox for multidimensional electroencephalography data - ScienceDirect

Materials July-2 2022 - Browse Articles

Spatial Congruence Analysis (SCAN): An objective method for detecting biogeographical patterns based on species' range congruences

Global patterns of climate change impacts on desert bird communities

Frontiers A Practical Guide to Sparse k-Means Clustering for Studying Molecular Development of the Human Brain

A standardized dataset for conservation prioritization of songbirds to support CITES - ScienceDirect

Classification-Based Anomaly Detection for General Data

Publications Perceiving Systems - Max Planck Institute for Intelligent Systems

MHP v2.0 Benchmark (Multi-Human Parsing)