8 research outputs found

    Style and Pose Control for Image Synthesis of Humans from a Single Monocular View

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    Photo-realistic re-rendering of a human from a single image with explicit control over body pose, shape and appearance enables a wide range of applications, such as human appearance transfer, virtual try-on, motion imitation, and novel view synthesis. While significant progress has been made in this direction using learning-based image generation tools, such as GANs, existing approaches yield noticeable artefacts such as blurring of fine details, unrealistic distortions of the body parts and garments as well as severe changes of the textures. We, therefore, propose a new method for synthesising photo-realistic human images with explicit control over pose and part-based appearance, i.e., StylePoseGAN, where we extend a non-controllable generator to accept conditioning of pose and appearance separately. Our network can be trained in a fully supervised way with human images to disentangle pose, appearance and body parts, and it significantly outperforms existing single image re-rendering methods. Our disentangled representation opens up further applications such as garment transfer, motion transfer, virtual try-on, head (identity) swap and appearance interpolation. StylePoseGAN achieves state-of-the-art image generation fidelity on common perceptual metrics compared to the current best-performing methods and convinces in a comprehensive user study

    Neural Actor: Neural Free-view Synthesis of Human Actors with Pose Control

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    We propose Neural Actor (NA), a new method for high-quality synthesis of humans from arbitrary viewpoints and under arbitrary controllable poses. Our method is built upon recent neural scene representation and rendering works which learn representations of geometry and appearance from only 2D images. While existing works demonstrated compelling rendering of static scenes and playback of dynamic scenes, photo-realistic reconstruction and rendering of humans with neural implicit methods, in particular under user-controlled novel poses, is still difficult. To address this problem, we utilize a coarse body model as the proxy to unwarp the surrounding 3D space into a canonical pose. A neural radiance field learns pose-dependent geometric deformations and pose- and view-dependent appearance effects in the canonical space from multi-view video input. To synthesize novel views of high fidelity dynamic geometry and appearance, we leverage 2D texture maps defined on the body model as latent variables for predicting residual deformations and the dynamic appearance. Experiments demonstrate that our method achieves better quality than the state-of-the-arts on playback as well as novel pose synthesis, and can even generalize well to new poses that starkly differ from the training poses. Furthermore, our method also supports body shape control of the synthesized results

    Innovation Agents

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    The standard narrative of entrepreneurship is one of self-employed creative individuals working out of their garage or independently owned start-up companies. Intrapreneurship--where employees are responsible for being alert to new opportunities inside firms--is another model for developing innovations. Relatively little is known, however, about the latter process through which large, complex firms engage in groundbreaking corporate entrepreneurship. This Article\u27s focus is on these types of innovation agents. It provides a thorough account of the positive and negative spillovers of intrapreneurial firms while making the following key points: First, intrapreneurial companies utilize their economies of scale, scope, and age to deliver innovations to the masses. They transform ideas, labor, and raw materials into tangible assets that can be traded in the market. Second, in doing so they offer individual entrepreneurs opportunities to capitalize their knowledge. Sustaining entrepreneurs\u27 prospects for supra-competitive profits is the main engine that motivates the latter to invest in discoveries in the first place. Lastly, intrapreneurial firms also serve as greenhouses for entrepreneurship through the migration of their own talented labor in the market. While these spillovers have tremendous societal benefits, they can also introduce harms. First, the race for the next breakthrough might result in anticompetitive behavior by rivals who conspire with employees-intrapreneurs to leave their firms and take with them confidential information. Second, intrapreneurs often aspire to undertake their own independent journey. In so doing, they leave secure positions and high salaries while carrying valuable knowledge and expertise. This, in return, often prompts intrapreneurial firms to act opportunistically and lock-in or lock-out intrapreneurs in restrictive and wasteful arrangements. As a solution, this Article proposes ways law can balance the positive and negative spillovers of intrapreneurship and ways the tax system can help achieve such result
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