Search Results for author:
Found 5 papers, 4 papers with code
AnthroNet: Conditional Generation of Humans via Anthropometrics
We present a novel human body model formulated by an extensive set of anthropocentric measurements, which is capable of generating a wide range of human body shapes and poses.
3D human pose and shape estimation
3D Human Reconstruction
+3
PSP-HDRI$+$: A Synthetic Dataset Generator for Pre-Training of Human-Centric Computer Vision Models
We introduce a new synthetic data generator PSP-HDRI$+$ that proves to be a superior pre-training alternative to ImageNet and other large-scale synthetic data counterparts.
PeopleSansPeople: A Synthetic Data Generator for Human-Centric Computer Vision
We found that pre-training a network using synthetic data and fine-tuning on various sizes of real-world data resulted in a keypoint AP increase of $+38. 03$ ($44. 43 \pm 0. 17$ vs. $6. 40$) for few-shot transfer (limited subsets of COCO-person train [2]), and an increase of $+1. 47$ ($63. 47 \pm 0. 19$ vs. $62. 00$) for abundant real data regimes, outperforming models trained with the same real data alone.
Unity Perception: Generate Synthetic Data for Computer Vision
We introduce the Unity Perception package which aims to simplify and accelerate the process of generating synthetic datasets for computer vision tasks by offering an easy-to-use and highly customizable toolset.
Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning
Unlike other benchmarks such as the Arcade Learning Environment, evaluation of agent performance in Obstacle Tower is based on an agent's ability to perform well on unseen instances of the environment.
