AI Researchers from Bytedance and the King Abdullah University of Science and Technology Present a Novel Framework For Animating Hair Blowing in Still Portrait Photos

Hair is among the most outstanding options of the human physique, impressing with its dynamic qualities that deliver scenes to life. Research have constantly demonstrated that dynamic parts have a stronger enchantment and fascination than static pictures. Social media platforms like TikTok and Instagram witness the each day sharing of huge portrait pictures as folks aspire to make their footage each interesting and artistically fascinating. This drive fuels researchers’ exploration into the realm of animating human hair inside nonetheless pictures, aiming to supply a vivid, aesthetically pleasing, and delightful viewing expertise.

Latest developments within the area have launched strategies to infuse nonetheless pictures with dynamic parts, animating fluid substances resembling water, smoke, and fireplace inside the body. But, these approaches have largely missed the intricate nature of human hair in real-life images. This text focuses on the inventive transformation of human hair inside portrait pictures, which includes translating the image right into a cinemagraph.

A cinemagraph represents an progressive brief video format that enjoys favor amongst skilled photographers, advertisers, and artists. It finds utility in varied digital mediums, together with digital commercials, social media posts, and touchdown pages. The fascination for cinemagraphs lies of their capability to merge the strengths of nonetheless pictures and movies. Sure areas inside a cinemagraph characteristic delicate, repetitive motions in a brief loop, whereas the rest stays static. This distinction between stationary and shifting parts successfully captivates the viewer’s consideration.

Via the transformation of a portrait photograph right into a cinemagraph, full with delicate hair motions, the concept is to boost the photograph’s attract with out detracting from the static content material, making a extra compelling and interesting visible expertise.

Present strategies and industrial software program have been developed to generate high-fidelity cinemagraphs from enter movies by selectively freezing sure video areas. Sadly, these instruments should not appropriate for processing nonetheless pictures. In distinction, there was a rising curiosity in still-image animation. Most of those approaches have centered on animating fluid parts resembling clouds, water, and smoke. Nevertheless, the dynamic habits of hair, composed of fibrous supplies, presents a particular problem in comparison with fluid parts. Not like fluid component animation, which has acquired intensive consideration, the animation of human hair in actual portrait pictures has been comparatively unexplored.

Animating hair in a static portrait photograph is difficult because of the intricate complexity of hair constructions and dynamics. Not like the graceful surfaces of the human physique or face, hair includes lots of of 1000’s of particular person elements, leading to advanced and non-uniform constructions. This complexity results in intricate movement patterns inside the hair, together with interactions with the pinnacle. Whereas there are specialised strategies for modeling hair, resembling utilizing dense digital camera arrays and high-speed cameras, they’re typically expensive and time-consuming, limiting their practicality for real-world hair animation.

The paper offered on this article introduces a novel AI methodology for routinely animating hair inside a static portrait photograph, eliminating the necessity for person intervention or advanced {hardware} setups. The perception behind this method lies within the human visible system’s decreased sensitivity to particular person hair strands and their motions in actual portrait movies, in comparison with artificial strands inside a digitalized human in a digital atmosphere. The proposed answer is to animate “hair wisps” as a substitute of particular person strands, making a visually pleasing viewing expertise. To attain this, the paper introduces a hair wisp animation module, enabling an environment friendly and automatic answer. An summary of this framework is illustrated under.

The important thing problem on this context is methods to extract these hair wisps. Whereas associated work, resembling hair modeling, has centered on hair segmentation, these approaches primarily goal the extraction of your entire hair area, which differs from the target. To extract significant hair wisps, the researchers innovatively body hair wisp extraction for instance segmentation drawback, the place a person phase inside a nonetheless picture corresponds to a hair wisp. By adopting this drawback definition, the researchers leverage occasion segmentation networks to facilitate the extraction of hair wisps. This not solely simplifies the hair wisp extraction drawback but in addition allows using superior networks for efficient extraction. Moreover, the paper presents the creation of a hair wisp dataset containing actual portrait pictures to coach the networks, together with a semi-annotation scheme to supply ground-truth annotations for the recognized hair wisps. Some pattern outcomes from the paper are reported within the determine under in contrast with state-of-the-art strategies.

This was the abstract of a novel AI framework designed to rework nonetheless portraits into cinemagraphs by animating hair wisps with pleasing motions with out noticeable artifacts. If you’re and wish to be taught extra about it, please be happy to consult with the hyperlinks cited under.

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