Abstract— Robot vision systems notoriously require large computing capabilities, rarely available on physical devices. Robots have limited embedded hardware, and almost all senso...
Roberto Pirrone, Giuseppe Careri, F. Saverio Fabia...
Markov Random Field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented u...
Marshall F. Tappen, Ce Liu, Edward H. Adelson, Wil...
Many successful models for predicting attention in a scene involve three main steps: convolution with a set of filters, a center-surround mechanism and spatial pooling to constru...
Naila Murray, Maria Vanrell, Xavier Otazu, C. Alej...
Markov random fields (MRFs) are popular and generic probabilistic models of prior knowledge in low-level vision. Yet their generative properties are rarely examined, while applica...
We describe a learning-based method for low-level vision problems--estimating scenes from images. We generate a synthetic world of scenes and their corresponding rendered images, m...