Search Results for author:
Found 7 papers, 4 papers with code
FOUND: Foot Optimization with Uncertain Normals for Surface Deformation Using Synthetic Data
Our FOUND approach tackles this, with 4 main contributions: (i) SynFoot, a synthetic dataset of 50, 000 photorealistic foot images, paired with ground truth surface normals and keypoints; (ii) an uncertainty-aware surface normal predictor trained on our synthetic dataset; (iii) an optimization scheme for fitting a generative foot model to a series of images; and (iv) a benchmark dataset of calibrated images and high resolution ground truth geometry.
FIND: An Unsupervised Implicit 3D Model of Articulated Human Feet
In this paper we present a high fidelity and articulated 3D human foot model.
Discrete neural representations for explainable anomaly detection
The aim of this work is to detect and automatically generate high-level explanations of anomalous events in video.
X-MAN: Explaining multiple sources of anomalies in video
In an effort to tackle this problem we make the following contributions: (1) we show how to build interpretable feature representations suitable for detecting anomalies with state of the art performance, (2) we propose an interpretable probabilistic anomaly detector which can describe the reason behind it's response using high level concepts, (3) we are the first to directly consider object interactions for anomaly detection and (4) we propose a new task of explaining anomalies and release a large dataset for evaluating methods on this task.
Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop
We introduce an automatic, end-to-end method for recovering the 3D pose and shape of dogs from monocular internet images.
Personalizing Human Video Pose Estimation
The outcome is a substantial improvement in the pose estimates for the target video using the personalized ConvNet compared to the original generic ConvNet.
Flowing ConvNets for Human Pose Estimation in Videos
The objective of this work is human pose estimation in videos, where multiple frames are available.
