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Found 7 papers, 1 papers with code
Statistical Feature-based Personal Information Detection in Mobile Network Traffic
Since the statistical features are independent of the value and type of personal information, the trained detector is capable of identifying various types of privacy leaks and obfuscated privacy leaks.
Discovering Interpretable Latent Space Directions of GANs Beyond Binary Attributes
In this way, arbitrary attributes can be edited by collecting positive data only, and the proposed method learns a controllable representation enabling manipulation of non-binary attributes like anime styles and facial characteristics.
Unified Shape and SVBRDF Recovery using Differentiable Monte Carlo Rendering
Reconstructing the shape and appearance of real-world objects using measured 2D images has been a long-standing problem in computer vision.
MaterialGAN: Reflectance Capture using a Generative SVBRDF Model
We address the problem of reconstructing spatially-varying BRDFs from a small set of image measurements.
A Bayesian Inference Framework for Procedural Material Parameter Estimation
Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability.
News Cover Assessment via Multi-task Learning
We propose an end-to-end multi-task learning network for image clarity assessment and semantic segmentation simultaneously, the results of which can be guided for news cover assessment.
Inverse Transport Networks
We introduce inverse transport networks as a learning architecture for inverse rendering problems where, given input image measurements, we seek to infer physical scene parameters such as shape, material, and illumination.
