Yuri on Ice is about hot dudes who ice skate and in a recent episode the two main dudes kissed and the Crowd. Went. Wild. For the past couple months since it first aired, audiences wondered whether the show would make good on its implicit premise: that this was a gay love story. And this implication came in several forms.
First, these dudes are almost incontrovertibly hot. Piercing eyes, flawless skin, athletic bods, expensive haircuts — the world of ice skating was kind of an ingenious setting for exhibiting these traits in a series’ characters. Ice skating is so much about performance (appearance being so much a part of performance) so these elements of the show’s character designs were blessed with narrative relevance (not that that’s inherently necessary; sometimes stupid hotness can be nothing more than stupid and hot and that’s fine.)
But the other sense in which the performance of ice skating paralleled the performance of the characters’ interior lives is in the performance of gender and sexuality. In one pivotal moment early in the series, Yuri — our starry-eyed lead on the quest for world championship — realises he needs to embrace his femininity to understand the concept of eros, which is the theme set for his routine by his new coach and eventual make-out bud, Victor.
Anime Feminist examines this scene well:
It isn’t until he’s going through Victor’s old costumes and finds one that’s meant to suggest “both male and female genders at once” that he realizes his problem: he’s been trying to play the aggressive playboy, when he should be playing the seductive femme fatale… On the ice, he’s able to give voice to a part of himself he hadn’t realized existed.
Yuri actually says at one point, while he’s performing in front of Victor, something along the lines of “I’ll be better than any woman for you.” In another, Yuri’s rival lets down his platinum blonde hair for a similar play at feminine beauty in pursuit of embodying another form of love: agape, a kind of unconditional love. The thrust here is that only when both characters abandon their notions of gender can they be actualised as something that transcends gender itself.
But it’s not just in those moments of epiphany that the show gets stuck into these ideas. The sexualisation is so overt and so normalised. Like, daaaaaamn:
In most anime (and media in general) a queer reading is left to subtext and critical inference, and these are vital particularly when so little media is intended by its author for queer audiences. But when that evidence becomes explicit, it brings a sense that the world is more broadly recognising queer audiences as these shows directly speak to them.
(I want to qualify this praise by linking to this post on Tumblr which describes just how utopian this vision of homosexuality is, and the privilege of that against Japan (and Russia’s) attitudes towards homosexuality in general.)
There’s a whole genre of Japanese art called yaoi (aka Boys Love or BL) which depicts male-on-male relationships and it’s typically authored by women, but yaoi is typically considered kind of abhorrent. The term of female fans of yaoi, for example, is fujoshi, which translates as “rotten women”, and even though fujoshi is self-deprecatory, it still denotes enjoying homosexual relationships as something perverse.
Despite that, Yuri on Ice has enjoyed a kind of critical acclaim no series like it has before. Part of why is there hasn’t really been a series like this before. There was Free! in 2013, but even though it hits some of the same notes (hot boys being lusty and sporty together), Free!’s gay subtext was much, much quieter than Yuri on Ice has been. And there is plenty of BL anime still being made (referred to by the typical fandom as “fujoshit.”) But Yuri on Ice combines those romantic sentiments with familiar shounen/seinen tropes — a young boy wanting to be The Very Best Like No One Ever Was while overcoming rivals and turning them into friends — and therefore sneaks into seeming like a very typical anime.
You only have to look at the credits to see how they pulled something like this off: it‘s directed by Sayo Yamamoto, who worked on several successful series which fronted powerful female characters (Michiko to Hatchin, Fujuko Mine) and is written by noted romance author Mitsurou Kubo. And while the studio behind them, MAPPA, is kind of a welterweight, they’ve already made a name for cult favourites with high production value. This isn’t a championship team, but it’s enough to get them in the competition, and between Kubo’s patience in building a realistic romance and Yamamoto’s ability to bring out the beauty of her characters, they were getting applause from the first round.
Yuri on Ice is enjoying the kind of love usually reserved for gritty, mature dramas or inventive genre subversions, usually from what are championship teams. Series like Psycho-Pass, Madoka Magica, and Monogatari, which have become prominent hallmarks of how good anime can be over the past five years, were all produced by some of the top writers, directors and studios in the entire medium. But this show has become so popular that real live championship figure skaters have been posting screenshots of it on Instagram. For as good as everyone agrees Madoka Magica and Kill la Kill were, few Actual Celebrities were tweeting about Soul Gems and Scissor Blades. The fact that an anime about gay figure skaters is being celebrated like this is unprecedented.
(That probably needs some qualification; like, Re:Zero was undeniably this year’s Biggest Series among anime fans, but again, it caught very little attention beyond weebs, and anyway it massively shit the bed in its second half, so seems destined to be remembered as fairly unexceptional.)
For queer audiences, including myself, stories like this provide a comfortable space in which to indulge in queerness and therefore begin to unravel decades of internalised homophobia and shame. In the same way a lot of us had our first experiences with heterosexuality through the fantasy of whatever was on the shelves at Video Ezy, which was then later challenged and refined through lived experiences, queer narratives in the mainstream erode the fear of taking that first step, and replace it with excitement.
Participating in this fandom is fun and exciting and yes, liberating, because getting to have exchanges like this:
…is so rare but reaffirming, especially about something as aggressively hetero as anime.
Yuri on Ice isn’t entirely utopian as a series. There’s issues worth noting here involving what constitutes beauty — everyone is conventionally attractive, i.e. thin, athletic, seductive — and with the championship focusing on male figure skating, female characters — although they often steal the scenes they’re in — are in too few scenes altogether. (It’s treatment of people of varying national backgrounds, however, is surprisingly mature.) But it’s a crucial step forward for anime, which has historically tokenised queer characters or presented them as gross parodies when not excluding them entirely. What’s more, anime communities like Reddit’s /r/anime, which have always been rotten with misogyny, racism and homophobia, are celebrating it. Whether that’s because those fans are finally figuring their shit out, or because a silent group have finally felt comfortable enough to find their voices, who knows. Ideally it’s both, but either way, it’s encouraging. And if it means more cleverly scripted, gorgeously animated queer stories are told, it’s worth celebrating too.
From Hayao Miyazaki’s Spirited Away to Satoshi Kon’s Paprika, Japanese anime has made it okay for adults everywhere to enjoy cartoons again. Now, a team of Tsinghua University and Cardiff University researchers have introduced CartoonGAN — an AI-powered technology that simulates the styles of Japanese anime maestri from snapshots of real world scenery.
Anime has distinct aesthetics, and traditional manual transformation techniques for real world scenes require considerable expertise and expense, as artists must painstakingly draw lines and shade colours by hand to create high-quality scene reproductions.
A real-world train station scene (left) transformed to a cartoon-style picture (right).
Meanwhile, existing transformation methods based on non-photorealistic rendering (NPR) or convolutional neural networks (CNN) are also either time-consuming or impractical as they require paired images for model training. Moreover, these methods do not produce satisfactory cartoonization results, as (1) different cartoon styles have unique characteristics involving high-level simplification and abstraction, and (2) cartoon images tend to have clear edges, smooth color shading and relatively simple textures, which present challenges for the texture-descriptor-based loss functions used in existing methods.
CartoonGAN is a GAN framework composed of two CNNs which enables style translation between two unpaired datasets: a Generator for mapping input images to the cartoon manifold; and a Discriminator for judging whether the image is from the target manifold or synthetic. Residual blocks are introduced to simplify the training process.
To avoid slow convergence and obtain high-quality stylization, dedicated semantic content loss and edge-promoting adversarial loss functions and an initialization phase are integrated into this cartoonization architecture. The content loss is defined using the ℓ1 sparse regularization (instead of the ℓ2 norm) of VGG (Visual Geometry Group) feature maps between the input photo and the generated cartoon image.
An example of a Makoto Shinkai stylization shows the importance of each component in CartoonGAN: The initialization phase performs a fast convergence to reconstruct the target manifold; sparse regularization copes with style differences between cartoon images and real-world photos while retaining original contents, and the adversarial loss function creates the clear edges.
Changing components in the CartoonGAN loss function: (a) input photo, (b) without initialization process, © using ℓ2 regularization for content loss, (d) removing edge loss, (e) CartoonGAN result.
Both real-world photos and cartoon images are used for model training, while the test data contains only real-world pictures. All training images are resized to 256×256 pixels. Researchers downloaded 6,153 real-world pictures from Flickr, 5,402 of which were for training and the rest for testing. A total of 14,704 cartoon images from popular anime artists Makoto Shinkai, Mamoru Hosoda, Hayao Miyazaki, and Satoshi Kon were used for model training.
Compared to recently proposed CNN-based image transformation frameworks CycleGAN or Gatys et al’s Neural Style Transfer (NST) method, CartoonGAN more successfully reproduces clear edges and smooth shading while accurately retaining the input photo’s original content.
Because NST only uses a single stylization reference image for model training, it cannot deeply learn a particular anime style, especially when there are significant content differences between the styli
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