4 accepted papers
Model-Based Reinforcement Learning (MBRL) leverages latent imagination for sample efficiency, yet remains constrained by **Historical Tethering**: imagination is typically initialized from observed states. This creates a learning asymmetry, where the world model’s manifold discovery outpaces the pol…
Motion blur arises when rapid scene changes occur during the exposure period, collapsing rich intra-exposure motion into a single RGB frame. Without explicit structural or temporal cues, RGB-only deblurring is highly ill-posed and often fails under extreme motion. Inspired by the human visual system
Recording and reconstructing high-speed scenes poses a significant challenge. While high-speed cameras can capture fine temporal details, their extremely high bandwidth demands make continuous recording unsustainable. Conversely, traditional RGB cameras, typically operating at 30 FPS, rely on frame…
Text-guided 3D face synthesis has achieved remarkable results by leveraging text-to-image (T2I) diffusion models. However most existing works focus solely on the direct generation ignoring the editing restricting them from synthesizing customized 3D faces through iterative adjustments. In this paper…