7 accepted papers
Single-image reflection removal (SIRR) is a highly ill-posed and computationally demanding problem. Existing CNN or Transformer-based methods often rely on large receptive fields and heavy computation, limiting their deployment on resource-constrained devices. To address this, we propose LightRR, a
Deep unrolling models (DUMs) have shown great poten-tial in sparse-view CT reconstruction by combining itera-tive optimization and deep learning. However, most DUMsinsufficiently account for physical degradation from sparse-view imaging, leading to slow convergence and persistentartifacts. To addres
Neural Radiance Fields (NeRF) has been widely used in computer vision and graphics, achieving impressive results in novel view synthesis and multi-view 3D reconstruction. However, despite its excellent performance under ideal conditions, NeRF struggles in challenging environments such as hazy, foggy…
Blurry video frame interpolation (BVFI), which aims to generate high-frame-rate clear videos from low-frame-rate blurry inputs, is a challenging yet significant task in computer vision. Current state-of-the-art approaches typically rely on linear or quadratic models to estimate intermediate motion.…
In recent years, depth recovery based on deep networks has achieved great success. However, the existing state-of-the-art network designs perform like black boxes in depth recovery tasks, lacking a clear mechanism. Utilizing the property that there is a large amount of non-local common characteristi…
Foveal Avascular Zone (FAZ) is a crucial indicator for retinal disease detection and accurate automatic FAZ segmentation has a significant impact in clinical applications. Apart from the binary FAZ segmentation map, a vessel segmentation map can provide further information. To simultaneously impleme…
Multimodal image registration plays an important role in diagnosing and treating ophthalmologic diseases. In this paper, a deep learning framework for multimodal retinal image registration is proposed. The framework consists of a segmentation network, feature detection and description network, and a…