By decomposing the image formation process into a sequential application of denoising
autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image …

Sparse-view computed tomography (CT)---using a small number of projections for
tomographic reconstruction---enables much lower radiation dose to patients and …

Image Inpainting has recently become an important research problem due to the rise of
generative image synthesis models. While many solutions have been proposed for this …

Adversarial patch attacks are an emerging security threat for real world deep learning
applications. We present Demasked Smoothing, the first approach (up to our knowledge) to …

Our brain can effortlessly recognize objects even when partially hidden from view. Seeing
the visible of the hidden is called amodal completion; however this task remains a challenge …

Blurry appearance of fast moving objects in video frames was successfully used to
reconstruct the object appearance and motion in both 2D and 3D domains. The proposed …

Generating background scenes for salient objects plays a crucial role across various
domains including creative design and e-commerce as it enhances the presentation and …

In this work, we introduce a challenging image restoration task, referred to as SuperInpaint,
which aims to reconstruct missing regions in low-resolution images and generate completed …

Image inpainting, which refers to the synthesis of missing regions in an image, can help
restore occluded or degraded areas and also serve as a precursor task for self-supervision …

Implicit representation of an image can map arbitrary coordinates in the continuous domain
to their corresponding color values, presenting a powerful capability for image …