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SIDGAN: High-Resolution Dubbed Video Generation via Shift-Invariant Learning
Dubbed video generation aims to accurately synchronize mouth movements of a given facial video with driving audio while preserving identity and scene-specific visual dynamics, such as head pose and lighting.
Individual Treatment Effect Estimation Through Controlled Neural Network Training in Two Stages
We develop a Causal-Deep Neural Network (CDNN) model trained in two stages to infer causal impact estimates at an individual unit level.
Learning Discriminative Relational Features for Sequence Labeling
For learning features derived from inputs at a particular sequence position, we propose a Hierarchical Kernels-based approach (referred to as Hierarchical Kernel Learning for Structured Output Spaces - StructHKL).
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