Our team will be presenting at CVPR 2018 on the topic of intrinsic image decomposition. Congratulations to our team members on this great achievement and thank for all the hard work in the past months! Together we keep pushing the boundaries of computer vision technologies and research.

Abstract. In this paper, the aim is to exploit the best of the two worlds. A method is proposed that (1) is empowered by deep learning capabilities, (2) considers a physics-based
reflection model to steer the learning process, and (3) exploits the traditional approach to obtain intrinsic images by exploiting reflectance and shading gradient information.
The proposed model is fast to compute and allows for the integration of all intrinsic components. To train the new model, an object centered large-scale datasets with intrinsic
ground-truth images are created.

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