![]() The full app costs $2.99.Ĭolor Name is an AR app that allows you to identify colors by simply pointing your iPhone towards an object. The only limitation of the app is that you need to purchase the full app to be able to share the palettes. You can create a color scheme of up to 11 different colors and the best part of this app is that you can use your existing pictures to create a color palette. It has plenty of templates that you can just pick up and start using in your projects. There are two ways to create a color palette using the hue chart, and using a photo. IColors is a simple color palette app that lets you create a color scheme from a photo. The work will be presented at the European Conference on Computer Vision (ECCV) in Munich, Germany taking place on September 8-14.For: Generating Color Palettes from photos In the future, we will explore how to incorporate mid level and high-level vision cues, such as detection, tracking, semantic/instance segmentation, for temporal propagation.” Liu and the team stated in the paper. ![]() ![]() “The STPN provides a general method for propagating information over time in videos. “The images have fewer artifacts and the colors are more vibrant,” Liu said. The method also produces better quantitative results than several previous state-of-the-art methods, as explained in the work. Liu says the framework is fast and can achieve real time results. A light-weighted convolutional neural network guides the propagation according to the content of the frames. The framework named, the Switchable Temporal Propagation Network (STPN), contains a linear propagation module that can deliver various video properties such as color, high-dynamic-range components (HDR), and object masks from keyframes to all the other frames that do not contain such features. Taking the example of color and mask propagation, she pre-trained the model on synthesized frame pairs generated from the MS-COCO dataset and then fine-tuned the network on the ACT dataset which contains 7260 video sequences with about 600,000 frames. Using NVIDIA TITAN XP GPUs, Liu and her colleagues trained this hybrid network on hundreds of videos from multiple datasets for color, HDR, and mask propagation. What makes this work unique is that the consequent colorization can be achieved via an interactive method in which the user annotates a part of the image, resulting in the finished product. The convolutional neural network infers what the colors should be from just one colorized frame and fills in the color in the remaining frames. “Now, colorizing a full video can be easily achieved by annotating at sparse locations in only a few key-frames,” Liu stated. Such redundancy has been extensively studied in video compression and encoding, but is less explored for more advanced video processing such as colorizing a video,” said Sifei Liu, Researcher at NVIDIA and the author of this paper. “Videos contain highly redundant information between frames. But now, a new deep learning based algorithm developed by NVIDIA researchers promises to make the process a lot easier - the new framework allows visual artists to simply colorize one frame in a scene and the AI goes to work by colorizing the rest of the scene in real time. Manually colorizing black and white video is labor intensive and a tedious process.
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