Enhancing low-light image visibility is a critical task in computer vision since it helps to
improve input for high-level algorithms. High-quality images typically have clear structural …

Low-light image enhancement is an important task in the domain of computer vision. Images
taken under insufficient lighting conditions manifest low visibility and unknown noises which …

In this paper, we propose a simple yet effective self-supervised method called spatio-
temporal contrastive learning (ST-CL) for 3D skeleton-based action recognition. ST-CL …

To enhance infrared images' contrast and visual effect, this paper proposes a contrast
enhancement method based on adaptive histogram correction and equalization. Unlike the …

In this paper, we present a method to compute energy-aware images, that aims to reduce
the energy consumption of displays. This method relies on a lightweight unsupervised deep …

The consumption of a video requires a considerable amount of energy during the various
stages of its life-cycle. With a billion hours of video consumed daily, this contributes …

Autonomous mobile agents (eg, mobile ground robots and UAVs) typically require low-
power/energy-efficient machine learning (ML) algorithms to complete their ML-based tasks …

Producing a high dynamic range (HDR) image from two low dynamic range (LDR) images
with extreme exposures is challenging due to the lack of well-exposed contents. Existing …

The mass adoption of display devices calls for advanced power-reduction techniques.
Power-constrained contrast enhancement (PCCE) gains many improvements in recent …

Displaying video content requires significant amounts of energy. In face of the energy crisis
and climate emergency, we propose a new approach to produce energy-aware images. The …