SIGGRAPH 2016 论文列表

Realistic materials have recently begun to be rendered in computer graphics. The realistic presentation of materials is essential for confirming color and gloss of a product in rapid prototyping and internet shopping. In addition, it enhances various immersive experiences in art, media, and augmented reality.

This article defines a new way to perform intuitive and geometrically faithful regressions on histogram-valued data. It leverages the theory of optimal transport, and in particular the definition of Wasserstein barycenters, to introduce for the first time the notion of barycentric coordinates for histograms. These coordinates take into account the underlying geometry of the ground space on which the histograms are defined, and are thus particularly meaningful for applications in graphics to shapes, color or material modification. Beside this abstract construction, we propose a fast numerical optimization scheme to solve this backward problem (finding the barycentric coordinates of a given histogram) with a low computational overhead with respect to the forward problem (computing the barycenter). This scheme relies on a backward algorithmic differentiation of the Sinkhorn algorithm which is used to optimize the entropic regularization of Wasserstein barycenters. We showcase an illustrative set of applications of these Wasserstein coordinates to various problems in computer graphics: shape approximation, BRDF acquisition and color editing.

We propose a unified motion planner that reproduces variations in swimming styles based on the differences in the fish skeletal structures or the variations in the swimming styles based on changes in environmental conditions. The key idea in our method, based on biology, is the following. We considered the common decision-making mechanism in fish that allows them to instantly decide "where and how to swim." The unified motion planner comprises two stages. In the first stage, where to swim to is decided. Using a probability distribution generated by integrating the perceptual information, the short-term target position and target speed are decided. In the second stage, how to swim is decided. A style of swimming that matches the information for transitioning from the current speed to the target speed is selected. Using the proposed method, we demonstrate 12 types of CG models with completely different sizes and skeletal structures, such as manta ray, tuna, and boxfish, as well as a scene where a school of a few thousand fish swim realistically. Our method is easy to integrate into existing graphics pipelines. In addition, in our method, the movement characteristics can easily be changed by adjusting the parameters. The method also has a feature where the expression of an entire school of fish, such as tornado or circling, can be designated top-down.

People may look dramatically different by changing their hair color, hair style, when they grow older, in a different era style, or a different country or occupation. Some of those may transfigure appearance and inspire creative changes, some not, but how would we know without physically trying? We present a system that enables automatic synthesis of limitless numbers of appearances. A user inputs one or more photos (as many as they like) of his or her face, text queries an appearance of interest (just like they'd search an image search engine) and gets as output the input person in the queried appearance. Rather than fixing the number of queries or a dataset our system utilizes all the relevant and searchable images on the Internet, estimates a doppelgänger set for the inputs, and utilizes it to generate composites. We present a large number of examples on photos taken with completely unconstrained imaging conditions.

This paper explores methods for synthesizing physics-based bubble sounds directly from two-phase incompressible simulations of bubbly water flows. By tracking fluid-air interface geometry, we identify bubble geometry and topological changes due to splitting, merging and popping. A novel capacitance-based method is proposed that can estimate volume-mode bubble frequency changes due to bubble size, shape, and proximity to solid and air interfaces. Our acoustic transfer model is able to capture cavity resonance effects due to near-field geometry, and we also propose a fast precomputed bubble-plane model for cheap transfer evaluation. In addition, we consider a bubble forcing model that better accounts for bubble entrainment, splitting, and merging events, as well as a Helmholtz resonator model for bubble popping sounds. To overcome frequency bandwidth limitations associated with coarse resolution fluid grids, we simulate micro-bubbles in the audio domain using a power-law model of bubble populations. Finally, we present several detailed examples of audiovisual water simulations and physical experiments to validate our frequency model.

We present a technique to synthesize time-varying weathered textures. Given a single texture image as input, the degree of weathering at different regions of the input texture is estimated by prevalence analysis of texture patches. This information then allows to gracefully increase or decrease the popularity of weathered patches, simulating the evolution of texture appearance both backward and forward in time. Our method can be applied to a wide variety of different textures since the reaction of the material to weathering effects is physically-oblivious and learned from the input texture itself. The weathering process evolves new structures as well as color variations, providing rich and natural results. In contrast with existing methods, our method does not require any user interaction or assistance. We demonstrate our technique on various textures, and their application to time-varying weathering of 3D scenes. We also extend our method to handle multi-layered textures, weathering transfer, and interactive weathering painting.

We present the Sketchy database , the first large-scale collection of sketch-photo pairs. We ask crowd workers to sketch particular photographic objects sampled from 125 categories and acquire 75,471 sketches of 12,500 objects. The Sketchy database gives us fine-grained associations between particular photos and sketches, and we use this to train cross-domain convolutional networks which embed sketches and photographs in a common feature space. We use our database as a benchmark for fine-grained retrieval and show that our learned representation significantly outperforms both hand-crafted features as well as deep features trained for sketch or photo classification. Beyond image retrieval, we believe the Sketchy database opens up new opportunities for sketch and image understanding and synthesis.

Reinforcement learning offers a promising methodology for developing skills for simulated characters, but typically requires working with sparse hand-crafted features. Building on recent progress in deep reinforcement learning (DeepRL), we introduce a mixture of actor-critic experts (MACE) approach that learns terrain-adaptive dynamic locomotion skills using high-dimensional state and terrain descriptions as input, and parameterized leaps or steps as output actions. MACE learns more quickly than a single actor-critic approach and results in actor-critic experts that exhibit specialization. Additional elements of our solution that contribute towards efficient learning include Boltzmann exploration and the use of initial actor biases to encourage specialization. Results are demonstrated for multiple planar characters and terrain classes.

High quality locomotion is key to achieving believable character animation, but is often modeled as a generic stepping motion between two locations. In practice, locomotion often has task-specific characteristics and can exhibit a rich vocabulary of step types, including side steps, toe pivots, heel pivots, and intentional foot slides. We develop a model for such types of behaviors, based on task-specific foot-step plans that act as motion templates. The footstep plans are invoked and optimized at interactive rates and then serve as the basis for producing full body motion. We demonstrate the production of high-quality motions for three tasks: whiteboard writing, moving boxes, and sitting behaviors. The model enables retargeting to characters of varying proportions by yielding motion plans that are appropriately tailored to these proportions. We also show how the task effort or duration can be taken into account, yielding coarticulation behaviors.

While the concept of visual saliency has been previously explored in the areas of mesh and image processing, saliency detection also applies to other sensory stimuli. In this paper, we explore the problem of tactile mesh saliency, where we define salient points on a virtual mesh as those that a human is more likely to grasp, press, or touch if the mesh were a real-world object. We solve the problem of taking as input a 3D mesh and computing the relative tactile saliency of every mesh vertex. Since it is difficult to manually define a tactile saliency measure, we introduce a crowdsourcing and learning framework. It is typically easy for humans to provide relative rankings of saliency between vertices rather than absolute values. We thereby collect crowdsourced data of such relative rankings and take a learning-to-rank approach. We develop a new formulation to combine deep learning and learning-to-rank methods to compute a tactile saliency measure. We demonstrate our framework with a variety of 3D meshes and various applications including material suggestion for rendering and fabrication.

Filigrees are thin patterns found in jewelry, ornaments and lace fabrics. They are often formed of repeated base elements manually composed into larger, delicate patterns. Digital fabrication simplifies the process of turning a virtual model of a filigree into a physical object. However, designing a virtual model of a filigree remains a time consuming and challenging task. The difficulty lies in tightly packing together the base elements while covering a target surface. In addition, the filigree has to be well connected and sufficiently robust to be fabricated. We propose a novel approach automating this task. Our technique covers a target surface with a set of input base elements, forming a filigree strong enough to be fabricated. We exploit two properties of filigrees to make this possible. First, as filigrees form delicate traceries they are well captured by their skeleton. This affords for a simpler definition of operators such as matching and deformation. Second, instead of seeking for a perfect packing of the base elements we relax the problem by allowing appearance preserving partial overlaps. We optimize a filigree by a stochastic search, further improved by a novel boosting algorithm that records and reuses good configurations discovered during the process. We illustrate our technique on a number of challenging examples reproducing filigrees on large objects, which we manufacture by 3D printing. Our technique affords for several user controls, such as the scale and orientation of the elements.

We propose a novel surface-only technique for simulating incompressible, inviscid and uniform-density liquids with surface tension in three dimensions. The liquid surface is captured by a triangle mesh on which a Lagrangian velocity field is stored. Because advection of the velocity field may violate the incompressibility condition, we devise an orthogonal projection technique to remove the divergence while requiring the evaluation of only two boundary integrals. The forces of surface tension, gravity, and solid contact are all treated by a boundary element solve, allowing us to perform detailed simulations of a wide range of liquid phenomena, including waterbells, droplet and jet collisions, fluid chains, and crown splashes.

This paper introduces a new computational method to solve differential equations on subdivision surfaces. Our approach adapts the numerical framework of Discrete Exterior Calculus (DEC) from the polygonal to the subdivision setting by exploiting the refin-ability of subdivision basis functions. The resulting Subdivision Exterior Calculus (SEC) provides significant improvements in accuracy compared to existing polygonal techniques, while offering exact finite-dimensional analogs of continuum structural identities such as Stokes' theorem and Helmholtz-Hodge decomposition. We demonstrate the versatility and efficiency of SEC on common geometry processing tasks including parameterization, geodesic distance computation, and vector field design.

We present an approach to example-based stylization of 3D renderings that better preserves the rich expressiveness of hand-created artwork. Unlike previous techniques, which are mainly guided by colors and normals, our approach is based on light propagation in the scene. This novel type of guidance can distinguish among context-dependent illumination effects, for which artists typically use different stylization techniques, and delivers a look closer to realistic artwork. In addition, we demonstrate that the current state of the art in guided texture synthesis produces artifacts that can significantly decrease the fidelity of the synthesized imagery, and propose an improved algorithm that alleviates them. Finally, we demonstrate our method's effectiveness on a variety of scenes and styles, in applications like interactive shading study or autocompletion.

Human motion is complex and difficult to synthesize realistically. Automatic style transfer to transform the mood or identity of a character's motion is a key technology for increasing the value of already synthesized or captured motion data. Typically, state-of-the-art methods require all independent actions observed in the input to be present in a given style database to perform realistic style transfer. We introduce a spectral style transfer method for human motion between independent actions, thereby greatly reducing the required effort and cost of creating such databases. We leverage a spectral domain representation of the human motion to formulate a spatial correspondence free approach. We extract spectral intensity representations of reference and source styles for an arbitrary action, and transfer their difference to a novel motion which may contain previously unseen actions. Building on this core method, we introduce a temporally sliding window filter to perform the same analysis locally in time for heterogeneous motion processing. This immediately allows our approach to serve as a style database enhancement technique to fill-in non-existent actions in order to increase previous style transfer method's performance. We evaluate our method both via quantitative experiments, and through administering controlled user studies with respect to previous work, where significant improvement is observed with our approach.

This paper presents Soli , a new, robust, high-resolution, low-power, miniature gesture sensing technology for human-computer interaction based on millimeter-wave radar. We describe a new approach to developing a radar-based sensor optimized for human-computer interaction, building the sensor architecture from the ground up with the inclusion of radar design principles, high temporal resolution gesture tracking, a hardware abstraction layer (HAL), a solid-state radar chip and system architecture, interaction models and gesture vocabularies, and gesture recognition. We demonstrate that Soli can be used for robust gesture recognition and can track gestures with sub-millimeter accuracy, running at over 10,000 frames per second on embedded hardware.