Multilayer feedforward networks are universal approximators
Neural Networks
A physical approach to color image understanding
International Journal of Computer Vision
Universal approximation using radial-basis-function networks
Neural Computation
Estimation of Illuminant Direction, Albedo, and Shape from Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
Measuring and modeling anisotropic reflection
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
Three-dimensional shape from color photometric stereo
International Journal of Computer Vision
Shape from shading with a generalized reflectance map model
Computer Vision and Image Understanding
Illumination for computer generated pictures
Communications of the ACM
Shape from Shading for Non-Lambertian Surfaces from One Color Image
ICPR '96 Proceedings of the 1996 International Conference on Pattern Recognition (ICPR '96) Volume I - Volume 7270
Enhanced 3D Shape Recovery Using the Neural-Based Hybrid Reflectance Model
Neural Computation
Shape recovery from shading by a new neural-based reflectance model
IEEE Transactions on Neural Networks
Learning parametric specular reflectance model by radial basis function network
IEEE Transactions on Neural Networks
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In this Letter, a new methodology for Colour Shape From Shading problem is proposed. The problem of colour SFS refers to the well-known fact that most real objects usually contain mixtures of diffuse and specular colour reflections. In this paper, these limitations are addressed and a new colour neural based model is proposed. The proposed approach focuses on developing a generalized neural based colour reflectance model. Experimental results on synthetic coloured objects and a real coloured object were performed to demonstrate the performance of the proposed methodology.