UNIST has been selected to participate in the ‘AI Star Fellowship‘ project, a key initiative supported by the Ministry of Science and ICT (MSIT) aimed at nurturing top-tier early-career AI researchers and fostering innovation ac... Read More
Abstract Dynamic MRI reconstruction, one of inverse problems, has seen a surge by the use of deep learning techniques. Especially, the practical difficulty of obtaining ground truth data has led to the emergence of unsupervised learning app... Read More
Abstract Meta reinforcement learning aims to develop policies that generalize to unseen tasks sampled from a task distribution. While context-based meta-RL methods improve task representation using task latents, they often struggle with out... Read More
Abstract While prior methods in Continuous Spatial-Temporal Video Super-Resolution (C-STVSR) employ Implicit Neural Representation (INR) for continuous encoding, they often struggle to capture the complexity of video data, relying on simple... Read More
Abstract Reconstructing 3Ds of hand-object interaction (HOI) is a fundamental problem that can find numerous applications. Despite recent advances, there is no comprehensive pipeline yet for bimanual class-agnostic interaction reconstructio... Read More
On May 21, UNIST held an appointment ceremony for Ji Young Lee, a distinguished social studies instructor, officially appointing her as a Collaborating Professor in the Graduate School of Artificial Intelligence. The three-year appointment... Read More
Abstract Learning with multiple modalities has recently demonstrated significant gains in many domains by maximizing the shared information across modalities. However, the current approaches strongly rely on high-quality paired datasets, wh... Read More
Abstract Investigating flat minima on loss surfaces in parameter space is well-documented in the supervised learning context, highlighting its advantages for model generalization. However, limited attention has been paid to the reinforcemen... Read More
Abstract Despite recent advancements in federated learning (FL), the integration of generative models into FL has been limited due to challenges such as high communication costs and unstable training in heterogeneous data environments. To a... Read More
Abstract Significant advancements have been achieved in the realm of understanding poses and interactions of two hands manipulating an object. The emergence of augmented reality (AR) and virtual reality (VR) technologies has heightened the... Read More
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