14 research outputs found
Sketch-A-Shape: Zero-Shot Sketch-to-3D Shape Generation
Significant progress has recently been made in creative applications of large
pre-trained models for downstream tasks in 3D vision, such as text-to-shape
generation. This motivates our investigation of how these pre-trained models
can be used effectively to generate 3D shapes from sketches, which has largely
remained an open challenge due to the limited sketch-shape paired datasets and
the varying level of abstraction in the sketches. We discover that conditioning
a 3D generative model on the features (obtained from a frozen large pre-trained
vision model) of synthetic renderings during training enables us to effectively
generate 3D shapes from sketches at inference time. This suggests that the
large pre-trained vision model features carry semantic signals that are
resilient to domain shifts, i.e., allowing us to use only RGB renderings, but
generalizing to sketches at inference time. We conduct a comprehensive set of
experiments investigating different design factors and demonstrate the
effectiveness of our straightforward approach for generation of multiple 3D
shapes per each input sketch regardless of their level of abstraction without
requiring any paired datasets during training
International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.
Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist