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From Pixels to Response Maps: Discriminative Image Filtering for Face Alignment in the Wild.

, , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 37 (6): 1312-1320 (2015)

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XNOR-Net++: Improved binary neural networks., and . BMVC, page 62. BMVA Press, (2019)Principal component analysis of image gradient orientations for face recognition., , and . FG, page 553-558. IEEE Computer Society, (2011)Project-Out Cascaded Regression with an application to face alignment.. CVPR, page 3659-3667. IEEE Computer Society, (2015)Faster, Better and More Detailed: 3D Face Reconstruction with Graph Convolutional Networks., , , and . ACCV (5), volume 12626 of Lecture Notes in Computer Science, page 188-205. Springer, (2020)Object landmark discovery through unsupervised adaptation., and . NeurIPS, page 13498-13509. (2019)Bayesian Prompt Learning for Image-Language Model Generalization., , , , , , and . ICCV, page 15191-15200. IEEE, (2023)Two-Stage Convolutional Part Heatmap Regression for the 1st 3D Face Alignment in the Wild (3DFAW) Challenge., and . ECCV Workshops (2), volume 9914 of Lecture Notes in Computer Science, page 616-624. (2016)Generic Active Appearance Models Revisited., , , and . ACCV (3), volume 7726 of Lecture Notes in Computer Science, page 650-663. Springer, (2012)Stochastic Process Regression for Cross-Cultural Speech Emotion Recognition., , , , and . Interspeech, page 3390-3394. ISCA, (2021)One-Shot Neural Face Reenactment via Finding Directions in GAN's Latent Space., , , , and . Int. J. Comput. Vis., 132 (8): 3324-3354 (August 2024)