To make computers get better at seeing —and not just seeing, but extracting high-level information—scientists have worked to recreate human vision in computers for the past 50 years.

Computer vision enables machines to interpret visual data instantly, mimicking human perception with greater accuracy and speed.

I would argue that computer vision’s focus on human data extraction does not merely coincide with these powerful interests, but rather is driven by them.

Machines are rapidly gaining the ability to perceive, interpret and interact with the visual world in ways that were once purely science fiction.

Human pose estimation stands as a pivotal area within computer vision, dedicated to identifying and localising human body keypoints in images or video sequences.

Despite advances in machine vision, processing visual data requires substantial computing resources and energy, limiting deployment in edge devices. Now, researchers from Japan have developed a ...

Given computer vision’s place as the cornerstone of an increasing number of applications from ADAS to medical diagnosis and robotics, it is critical that its weak points be mitigated, such as the ...

Researchers develop an energy-efficient device with near-human color discrimination capabilities, demonstrating great potential for computer vision applications.

Neuromorphic computing, which mimics the structure and function of biological neural systems, has thus emerged as a promising approach to overcome existing hurdles in computer vision.