3 accepted papers
Recent advances in Transformer-based Neural Operators have enabled significant progress in data-driven solvers for Partial Differential Equations (PDEs). Most current research has focused on reducing the quadratic complexity of attention to address the resulting low training and inference efficienc
Monocular endoscopic scene reconstruction is challenging due to limited viewpoints and interference from surgical instruments. While 3D Gaussian-based methods are popular for their strong reconstruction capabilities and efficiency, they often rely on sensors or stereo depth, resulting in blurred tis…
Image deblurring is an ill-posed task, where exists infinite feasible solutions for blurry images. Modem deep learning approaches usually discard the learning of blur kernels and directly employ end-to-end supervised learning. However, supervised learning can’t handle ill-posed tasks appropriately.…