The diffusion-based generative models have achieved remarkable success in text-based
image generation. However, since it contains enormous randomness in generation …

Tone‐mapping constitutes a key component within the field of high dynamic range (HDR)
imaging. Its importance is manifested in the vast amount of tone‐mapping methods that can …

We present a compact but effective CNN model for optical flow, called PWC-Net. PWC-Net
has been designed according to simple and well-established principles: pyramidal …

We present an algorithm for reconstructing dense, geometrically consistent depth for all
pixels in a monocular video. We leverage a conventional structure-from-motion …

We present a self-supervised learning approach for optical flow. Our method distills reliable
flow estimations from non-occluded pixels, and uses these predictions as ground truth to …

Feature warping is a core technique in optical flow estimation; however, the ambiguity
caused by occluded areas during warping is a major problem that remains unsolved. In this …

Applying image processing algorithms independently to each frame of a video often leads to
undesired inconsistent results over time. Developing temporally consistent video-based …

We propose the first deep learning approach for exemplar-based local colorization. Given a
reference color image, our convolutional neural network directly maps a grayscale image to …

We present a novel high-resolution face swapping method using the inherent prior
knowledge of a pre-trained GAN model. Although previous research can leverage …

With the rapid development of cartoon industry, various studies on two-dimensional (2D)
cartoon have been proposed for different application scenarios, such as quality assessment …