The astonishing development of single-photon cameras has created an unprecedented opportunity for scientific and industrial imaging. However, the high data throughput generated by these 1-bit sensors creates a significant bottleneck for low-power applications. In this paper, we explore the possibility of generating a color image from a single binary frame of a single-photon camera. We evidently find this problem being particularly difficult to standard colorization approaches due to the substantial degree of exposure variation. The core innovation of our paper is an exposure synthesis model framed under a neural ordinary differential equation (Neural ODE) that allows us to generate a continuum of exposures from a single observation. This innovation ensures consistent exposure in binary images that colorizers take on, resulting in notably enhanced colorization. We demonstrate applications of the method in single-image and burst colorization and show superior generative performance over baselines. Project website can be found at https://vishal-s-p.github.io/projects/2023/generative_quanta_color.html.

Palette.fm is a free artificial intelligence (AI) tool that can turn black-and-white photos into color. Thanks to machine learning, it can identify what is in an image and take a good guess at applying the right color. If you've never colorized black-and-white photos before, the results will blow you away! Unlike other AI colorizer tools, the image can be fine-tuned using a text prompt or by selecting a different color palette. If you have some old black-and-white family photos, this is how you can bring them to life in a matter of minutes.

For years, production companies have used costly techniques to colorize old black and white movies. But now artificial intelligence is placing that capability in the hands of everyday users, allowing you to add color to old family photos, historical images, or black and white video frames in seconds. It works like this: A developer feeds a large number of color images into a neural network, which is AI-speak for software modeled after brain functions. Over time, the software learns to recognize different objects and determine their likely colors. These algorithms are incorporated into online services as well as software that you can download and run on a computer.

Colorizer is a program that hypothesizes color values that represent a given word or sentence, taking into account both physical descriptions of objects and their emotional connotations. This new application of common sense reasoning uses background knowledge about the world to build a model of the connections between everyday things, and uses this model to guess an appropriate color for a word. Colorizer can run over either static text or real time input, such as a speech recognition stream. It has applications in games, the arts, and webpage design.