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Ballester, C., & Caselles V. (1998).  Lower Semicontinuity of the Affine Total Variation used in Image Segmentation. Rev. Matem. Union Matem. Argentina (num. Dedicado a J. Bouillet). 41(1), 41-60.
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Andreu, F., Ballester C., Caselles V., & Mazón J. M. (2001).  Minimizing total variation flow. Journal of Differential and Integral Equations. 4(3), 321–360.
Andreu, F., Ballester C., Caselles V., & Mazón J. M. (2000).  Minimizing total variation flow. Comptes Rendus de l'Académie des Sciences-Series I-Mathematics. 331(11), 867–872.
Rezaeirowshan, B., Ballester C., & Haro G. (2016).  Monocular Depth Ordering using Perceptual Occlusion Cues. International Conference on Computer Vision and Applications, VISAPP 2016.
Caselles, V., Sapiro G., Solé A., & Ballester C. (2004).  Morse description and morphological encoding of continuous data. SIAM Journal Multiscale Modeling & Simulation. 2(2), 179-209.
Oliver, M., Raad L., Ballester C., & Haro G. (2018).  Motion Inpainting by an Image-Based Geodesic AMLE Method. Proceedings of the 2018 25th IEEE International Conference on Image Processing (ICIP).
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Andreu, F., Ballester C., Caselles V., & Mazón J. M. (1999).  A Nonlinear Parabolic Equation Arising in Image Processing. Multiresolution, Computer Vision and PDE's. Foundations of Computational Mathematics.
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Vitoria, P., Sintes J., & Ballester C. (2018).  Semantic Image Inpainting Through Improved Wasserstein Generative Adversarial Networks. accepted as an oral presentation in International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) 2019.
Oliver, M., P.Palomares R., Ballester C., & Haro G. (2017).  Spatio-temporal binary video inpainting via threshold dynamics. International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
Vitoria, P., Fedorov V., & Ballester C. (2017).  Spatio-temporal tube segmentation through a video metrics-based patch similarity measure. Proceedings of the 19th Irish Machine Vision and Image Processing confence (IMVIP 2017), pp. 147-154.
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Ballester, C., & Gonzalez M. (1995).  Texture discrimination by variational methods. Second European Conference on Image Processing, Proceedings pp. 251-306.
Ballester, C., & Gonzalez M. (1996).  Texture segmentation by variational methods. ICAOS'96 Images, Wavelets and PDE's. 219, 187–193.
Vitoria, P., & Ballester C. (2018).  Towards Artifact-free Images through Perceptual Image Restoration. Poster presentation. In: ECCV 2018 Workshop and Challenge on Perceptual Image Restoration and Manipulation. September 8-14, 2018.
Ballester, C., Caselles V., & Monasse P. (2003).  The tree of shapes of an image. ESAIM CONTROLE OPTIMISATION ET CALCUL DES VARIATIONS. 9, 1-18.
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Ballester, C., Caselles V., Rougé B., & Verdera J. (2003).  Une méthode géométrique de fusion pour des images P+XS. Société Française de Photogrammétrie et de Télédétection. 169, 53-64 (Choosed one of the 5 best algorithms of P+XS image fusion by the French Spatial Agency CNES) .
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Ballester, C., Caselles V., & Verdera J. (2003).  A variational model for disocclusion. Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429), 2003, pp. III-677-80 vol.2.. 3, III–677.
Ballester, C., Caselles V., Verdera J., Bertalmio M., & Sapiro G. (2001).  A variational model for filling-in gray level and color images. Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on. 1, 10–16.
Ballester, C., Caselles V., Igual L., Rougé B., & Verdera J. (2006).  A Variational Model for P+XS Image Fusion . International Journal of Computer Vision. 69(1), 43-58.