4 accepted papers
Omnidirectional image super-resolution (ODISR) remains challenging due to extreme magnification factors (e.g., 8x, 16x) and projection-specific distortions, which degrade edge integrity and limit model performance. This paper proposes an edge-focused framework combined with spherical geometric augme
Microexpressions are expressions that people inadvertently express, and therefore often represent a person’s true emotion. However, because it has a low intensity and a short duration, it is hard to be recognized correctly. In this paper, we propose a deep learning magnification method to generate m…
Decentralized optimization is emerging as a viable alternative for scalable distributed machine learning, but also introduces new challenges in terms of synchronization costs. To this end, several communication-reduction techniques, such as non-blocking communication, quantization, and local step…
In this paper we propose a novel method of estimating indoor scenes from a single full-view image. On the one hand, the conventional methods cope with limited field of view images, such as perspective images and hemispherical omnidirectional images, which result in visually open boundary condition,…