This paper reviews the challenge on constrained high dynamic range (HDR) imaging that
was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held …

Three-dimensional integration offers architectural and performance benefits for scaling
augmented/virtual reality (AR/VR) models on highly resource-constrained edge devices …

HDR is an important part of computational photography technology. In this paper, we
propose a lightweight neural network called Efficient Attention-and-alignment-guided …

The world's push toward an environmentally sustainable society is highly dependent on the
semiconductor industry, due to carbon footprints of global-scale sources such as computing …

Convolutional neural network techniques have shown great promise in many low-level
image processing tasks. However, due to the reduced impact of convolution operations in …

Auxiliary features such as geometric buffers (G-buffers) and path descriptors (P-buffers)
have been shown to significantly improve Monte Carlo (MC) denoising. However, recent …

Abstract Graph Neural Networks (GNNs) have excelled in various graph-based applications.
Recently, knowledge distillation (KD) has provided a new approach to further boost GNNs …

Image denoising is a fundamental but critical task. Previous works based on deep networks
have made great progress, but suffer from the problem of computational overload. This …

For low-level computer vision and image processing ML tasks, training on large datasets is
critical for generalization. However, the standard practice of relying on real-world images …