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Found 13 papers, 0 papers with code
Anything in Any Scene: Photorealistic Video Object Insertion
Our proposed general framework encompasses three key processes: 1) integrating a realistic object into a given scene video with proper placement to ensure geometric realism; 2) estimating the sky and environmental lighting distribution and simulating realistic shadows to enhance the light realism; 3) employing a style transfer network that refines the final video output to maximize photorealism.
An End-to-end Food Portion Estimation Framework Based on Shape Reconstruction from Monocular Image
Dietary assessment is a key contributor to monitoring health status.
Image Based Food Energy Estimation With Depth Domain Adaptation
In this paper, we propose an "Energy Density Map" which is a pixel-to-pixel mapping from the RGB image to the energy density of the food.
Towards the Creation of a Nutrition and Food Group Based Image Database
Food classification is critical to the analysis of nutrients comprising foods reported in dietary assessment.
An Integrated System for Mobile Image-Based Dietary Assessment
Accurate assessment of dietary intake requires improved tools to overcome limitations of current methods including user burden and measurement error.
Improving Dietary Assessment Via Integrated Hierarchy Food Classification
Image-based dietary assessment refers to the process of determining what someone eats and how much energy and nutrients are consumed from visual data.
Towards Learning Food Portion From Monocular Images With Cross-Domain Feature Adaptation
We aim to estimate food portion size, a property that is strongly related to the presence of food object in 3D space, from single monocular images under real life setting.
An End-to-End Food Image Analysis System
Our end-to-end framework is evaluated on a real life food image dataset collected from a nutrition feeding study.
Visual Aware Hierarchy Based Food Recognition
Experimental results demonstrate that our system can significantly improve both classification and recognition performance on 4 publicly available datasets and the new VFN dataset.
Multi-Task Image-Based Dietary Assessment for Food Recognition and Portion Size Estimation
Deep learning based methods have achieved impressive results in many applications for image-based diet assessment such as food classification and food portion size estimation.
Incremental Learning In Online Scenario
Modern deep learning approaches have achieved great success in many vision applications by training a model using all available task-specific data.
Semi-Automatic Crowdsourcing Tool for Online Food Image Collection and Annotation
The web crawler is used to download large sets of online food images based on the given food labels.
Single-View Food Portion Estimation: Learning Image-to-Energy Mappings Using Generative Adversarial Networks
We can then estimate food energy based on the energy distribution.
