Ever heard of meitu xiu xiu? yeah, this app does wonders, from editing your face, hair, makeup and even the background. You can clean up your blemishes, conceal your dark eye circles and remove any unwanted object in the photo. Just one of the few things this app can do!
Meitu Xiu Xiu was created in March 2013 by Wu Xinhong, the CEO of Meitu. It was one of the apps from China. Meitu is a photo-centered app developer, which is founded in 2008 in Xiamen. Currently, the major revenue source of Meitu is advertising and it is making a small number of profits, disclosed by the CEO. The company was backed by Cai Wensheng, a well-known angel investor. The app has 52 million active daily users and 270 million monthly active users.[2]
Xiu-xiu Photo Editor Free Download
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Auto enhance focuses on the nature of photos taken, while Edit includes functions of cropping, rotation, sharpening and adjustment of ratio. For Enhance, users can apply slight adjustment on the photo by controlling the levels of brightness, contrast, colour temperature, saturation, highlight, shadow and smart light. Major types of filters are LOMO, Beauty, Style as well as Art. Different frames can be chosen from Poster, Simple and Fantasy. Magic Brush provides a great variety of brushes with different colours and patterns for users to decorate the photos. Mosaic brush enables users to cover certain parts of the photo. Texts can be added to the photo. Choices of different bubbles, font as well as style of words are available. Blurring effect is also available to make the photo less distinct and clear.
There are seven major functions for retouching a photo: automatic retouch, smooth and whiten skin, remove blemish, make slimmer, remove dark circles and bags under the eyes, make taller, and enhance the eyes.[4]
Template integrates photos in a vertical rectangle tightly. MeituPic has 15 frames or free download function for users. MeituPic also provides different templates according to number of photos inserted.
Meitu Xiu Xiu is a Chinese Photo Editor which is versatile and I think have all intermediate features I need for photo editing. You can make yourself slim you are fat. You can make yourself fat if you are skinny. You could make yourself become fair enough if you have a dark skin color [Refer pictures in 3rd rows]. The best thing I experience from Meitu Xiu Xiu is the features overlapping and the saving mode. You can apply all your editing at the end with all features before you save the pictures and you can redo any step you wish. Cool!!
Meitu Xiu Xiu also has an android version which it is also an ultimate & powerful in your mobile Android smartphone. In mobile version, it was a simplified version of desktop version. However, I think the features overlapping should be included in mobile version. I feel inconvenient to save few times of the pictures in order to apply few edit features. Maybe they should enhance it in future. Sharing is a must for any of social photo editing tool, so does Meitu Xiu Xiu. Sharing is simple and easy to Sina Weibo, RenRen Wang & QQ.
Thank you so much for finding this. It seems as though every gyaru edits their pics and I did not want to pay for photoshop! Haha the really scary thing is some girls I see on tumblr genuinely edit their pictures past point you have here and think it looks better.
Ever since the Chinese app launched back in 2008, Meitu has exploded in popularity around the world. So far, it's available in more than 26 countries and it's been downloaded 1.1 billion times. The app offers airbrushing tools and other visual editing for photos, as well as virtual makeup and stickers. While the app's interface is pretty intuitive and easy to use, there are a lot more options than many other photo editing apps that offer only filters or only stickers.
As a photographer and a huge fan of photo apps like VSCO and Instagram, I was pretty excited to add Meitu to my mobile folder of visual editing apps. Again, Meitu offers tons of alternatives besides just pre-designed filters. At the same time, editing photos manually can take up a lot of time that, quite frankly, many of us don't have during the day. It's nice to have different types of editing alternatives all in one single app like Meitu, depending on the amount of time I have and the different kinds of photos I'm looking to edit.
Go to the App Store on your smartphone and search for "Meitu." The first app that should show up has a pink icon with the Chinese character "xiu," which means "beautiful" or "elegant." This is Meitu. When you download Meitu and open then open the app on your phone, you'll see that the main page includes all of the photo editing options available, such as "Editing" and "Retouch." The latter has some astonishing options; for instance, you can make figures in the photo appear taller, get rid of acne, and even brighten dark circles (bye, bye, concealer!).
If you're looking to manually touch up a photo, the "Editing" option has a number of features that are relatively standard when it comes to photo editing, such as "auto," "brightness," "contrast," and "sharpen" (similar to what you can do on Instagram).
Again, swipe left on Meitu's main page and click on "Hand-drawn." The first page you'll see will show an example of what you can do to your photos with "Hand-drawn" (plus, it'll boast about how many times this particular feature has been used by Meitu fans). Click the pink button that asks you to "Try now."
I will point out that Meitu seems to conform to very narrow standards of beauty. For instance, one of the tips suggests that you need to have long hair in order to make the photo editing app work. Honestly, who cares? Ultimately, pick the selfie that you like the most.
Before editing, you'll have to give permission for Meitu to access your photo album and camera. Once you've done that, you can either take a photo and upload it directly to Meitu or select an existing photo from the album on your phone.
Once you've uploaded a photo, you can now begin applying filters to make your selfie look "hand-drawn!" The photo work station is up top, while a carousel of seven filters are at the bottom. Filters range from "Angelic" to "Fairy Tale" to "Petals." My app in particular notes that "Blossoms" is the most popular filter at the moment, and that "New Year" is a new filter. I'm hoping this means that Meitu will rotate different "hand-drawn" filters through its photo editing system.
The last thing to do in "Hand-drawn" is to decide if you want to share the photo with your friends on a variety of social media, such as Facebook, WeChat, or Instagram, or if you'd like to change the effect and use another filter (the one I'm using for this photo is the "Angelic" filter, in case you were wondering).
Granted, the final result doesn't look remotely anything like what I do in real life. But I guess nobody edits a photo to make it look realistic, right? If the "Hand-drawn" feature is a bit much, you can always go back to applying more subtle changes with the "Editing" option.
MG Belka is an award-winning journalist, photographer and editor currently based in Eugene, Oregon, where his doppelgnger also lives. He thinks people should stop using the term "guilty pleasure" and start listening to two-tone ska again. If he seems nervous, it's because he is.
A microfiber Fabry-Perot (FP) interferometer is proposed for photoacoustic sensing. It is fabricated by utilizing the 193 nm UV exposure and the phase mask technique. Two fiber Bragg gratings which are formed in a microscaled optical fiber as a FP cavity serves as a sensor. In contrast to the conventional, new characteristics are attributed to the microfiber segment of the refractive index change. The microfiber FP interferometric photoacoustic sensor dependencies on acoustic pressure, temperature, and refractive index are investigated. This compact photoacoustic sensor, with the diameter of microns, is suitable for photoacoustic imaging, especially in photo acoustic microtomography.
Abstract The creation of photorealistic virtual worlds requires the accurate modeling of 3D surface geometry for a wide range of objects. For this, meshes are appealing since they 1) enable fast physics-based rendering with realistic material and lighting, 2) support physical simulation, and 3) are memory-efficient for modern graphics pipelines. Recent work on reconstructing and statistically modeling 3D shape, however, has critiqued meshes as being topologically inflexible. To capture a wide range of object shapes, any 3D representation must be able to model solid, watertight, shapes as well as thin, open, surfaces. Recent work has focused on the former, and methods for reconstructing open surfaces do not support fast reconstruction with material and lighting or unconditional generative modelling. Inspired by the observation that open surfaces can be seen as islands floating on watertight surfaces, we parameterize open surfaces by defining a manifold signed distance field on watertight templates. With this parameterization, we further develop a grid-based and differentiable representation that parameterizes both watertight and non-watertight meshes of arbitrary topology. Our new representation, called Ghost-on-the-Shell (G-Shell), enables two important applications: differentiable rasterization-based reconstruction from multiview images and generative modelling of non-watertight meshes. We empirically demonstrate that G-Shell achieves state-of-the-art performance on non-watertight mesh reconstruction and generation tasks, while also performing effectively for watertight meshes.
Abstract Large text-to-image diffusion models have impressive capabilities in generating photorealistic images from text prompts. How to effectively guide or control these powerful models to perform different downstream tasks becomes an important open problem. To tackle this challenge, we introduce a principled finetuning method -- Orthogonal Finetuning (OFT), for adapting text-to-image diffusion models to downstream tasks. Unlike existing methods, OFT can provably preserve hyperspherical energy which characterizes the pairwise neuron relationship on the unit hypersphere. We find that this property is crucial for preserving the semantic generation ability of text-to-image diffusion models. To improve finetuning stability, we further propose Constrained Orthogonal Finetuning (COFT) which imposes an additional radius constraint to the hypersphere.Specifically, we consider two important finetuning text-to-image tasks: subject-driven generation where the goal is to generate subject-specific images given a few images of a subject and a text prompt, and controllable generation where the goal is to enable the model to take in additional control signals. We empirically show that our OFT framework outperforms existing methods in generation quality and convergence speed. 0852c4b9a8
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