Stroke-Based Stylization Learning and Rendering with Inverse Reinforcement Learning

Among various traditional art forms, brush stroke drawing is one of the widely used styles in modern computer graphic tools such as GIMP, Photoshop and Painter. In this paper, we develop an AI-aided art authoring (A4) system of non- photorealistic rendering that allows users to automatically generate brush stroke paintings in a specific artist’s style. Within the reinforcement learning framework of brush stroke generation proposed by Xie et al.[Xie et al., 2012], our contribution in this paper is to learn artists’ drawing styles from video-captured stroke data by inverse reinforcement learning. Through experiments, we demonstrate that our system can successfully learn artists’ styles and render pictures with consistent and smooth brush strokes

Browse-to-search

This demonstration presents a novel interactive online shopping application based on visual search technologies. When users want to buy something on a shopping site, they usually have the requirement of looking for related information from other web sites. Therefore users need to switch between the web page being browsed and other websites that provide search results. The proposed application enables users to naturally search products of interest when they browse a web page, and make their even causal purchase intent easily satisfied. The interactive shopping experience is characterized by: 1) in session - it allows users to specify the purchase intent in the browsing session, instead of leaving the current page and navigating to other websites; 2) in context - -the browsed web page provides implicit context information which helps infer user purchase preferences; 3) in focus - users easily specify their search interest using gesture on touch devices and do not need to formulate queries in search box; 4) natural-gesture inputs and visual-based search provides users a natural shopping experience. The system is evaluated against a data set consisting of several millions commercial product images. © 2012 Authors

Skeleton Based Parametric 2D Region Representation: Disk B-Spline Curves

The skeleton, or medial axis, is an important attribute of 2D shapes. The disk B-spline curve (DBSC) is a skeleton-based parametric freeform 2D region representation, which is defined in B-spline form. The DBSC describes not only a 2D region, which is suitable for describing heterogonous materials in the region, but also the center curve (skeleton) of the region explicitly, which is suitable for animation, simulation and recognition. In addition to being useful for error estimation of the B-spline curve, the DBSC can be used in designing and animating freeform 2D regions. Despite increasing DBSC applications, its theory and fundamentals have not been thoroughly investigated. In this paper, we discuss several fundamental properties and algorithms, such as the de Boor algorithm for DBSCs. We first derive the explicit evaluation and derivatives formulas at arbitrary points of a 2D region (interior and boundary) represented by a DBSC and then provide heterogeneous object representation. We also introduce modeling and interactive heterogeneous object design methods for a DBSC, which consolidates DBSC theory and supports its further applications

Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis

Deep person generation has attracted extensive research attention due to its wide applications in virtual agents, video conferencing, online shopping and art/movie production. With the advancement of deep learning, visual appearances (face, pose, cloth) of a person image can be easily generated or manipulated on demand. In this survey, we first summarize the scope of person generation, and then systematically review recent progress and technical trends in deep person generation, covering three major tasks: talking-head generation (face), pose-guided person generation (pose) and garment-oriented person generation (cloth). More than two hundred papers are covered for a thorough overview, and the milestone works are highlighted to witness the major technical breakthrough. Based on these fundamental tasks, a number of applications are investigated, e.g., virtual fitting, digital human, generative data augmentation. We hope this survey could shed some light on the future prospects of deep person generation, and provide a helpful foundation for full applications towards digital human

Water as Agent: Restoring Displaced Communities in Gulu, Uganda

Disasters due to war and conflict or natural forces are responsible for the 26 million people displaced across the world today. The crisis extends into the temporary, yet indefinite, displacement camps where people live in congested living arrangements, vulnerable to an increased risk of disease, death, and social violence (spousal abuse, rape). Even when chaos subsides, social and physical networks have frayed rendering the temporary displacement camp a permanent home for some. Often, despite this “permanence”, access to adequate services and infrastructure and hence social and economic growth remains in a state of emergency. This thesis proposes that water infrastructure is the key social catalyst for developing these displacement camps into permanent sustainable communities. An urban displacement camp in the town of Gulu, Northern Uganda, is the case study location for a speculative design intervention. During rebel activities from 1996 to 2004, the town of Gulu more than tripled in size, absorbing almost 100,000 displaced people forced to flee their land. These people settled in displacement camps next to, and within the wetlands that border the town on all sides. The urban metabolism of the town has become polluted as the displaced people use, alter and degrade the wetlands because they have no other alternatives. Following the instigation of a peace process in 2006, some people have begun the journey home. However, it is estimated that just over half of these people will continue to live in the squalid camps, without an opportunity to prosper. A strategy is proposed for addressing and subsequently re-defining this urban metabolism. By synthesizing the existing urban fabric with strategies for harnessing the natural landscape, varying scales of water infrastructure are proposed. New opportunities for agricultural production is supported, while the spatial relationships created by the physical structuring of the water infrastructure renews the influence that water collection and distribution has in creating the social locus of a community