Search Results for author:
Found 8 papers, 5 papers with code
SIGNet: Intrinsic Image Decomposition by a Semantic and Invariant Gradient Driven Network for Indoor Scenes
An ablation study is conducted showing that the use of the proposed priors and progressive CNN increase the IID performance.
PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition
An extensive ablation study and large scale experiments are conducted showing that it is beneficial for edge-driven hybrid IID networks to make use of illumination invariant descriptors and that separating global and local cues helps in improving the performance of the network.
Generative Models for Multi-Illumination Color Constancy
However, most of the existing color constancy methods are designed for single light sources.
EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes
Multimodal large-scale datasets for outdoor scenes are mostly designed for urban driving problems.
Novel View Synthesis from Single Images via Point Cloud Transformation
In this paper the argument is made that for true novel view synthesis of objects, where the object can be synthesized from any viewpoint, an explicit 3D shape representation isdesired.
ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition
The aim is to distinguish strong photometric effects from reflectance variations.
Color Constancy by GANs: An Experimental Survey
In this paper, we formulate the color constancy task as an image-to-image translation problem using GANs.
Joint Learning of Intrinsic Images and Semantic Segmentation
To that end, we propose a supervised end-to-end CNN architecture to jointly learn intrinsic image decomposition and semantic segmentation.
