Quadrupeds can generate various motor behaviors with the muscle synergies activated by the central nervous system. However, versatile locomotion for quadruped robots remains challenging due to the complexity of the high-dimensional limb dynamics with many physical constraints. Current approaches typically apply a dedicated policy or controller for each motor behavior, which requires the optimization of a large number of parameters and training process is complicated. In this paper, we propose a Generalist Agent Learning Architecture (GALA) to learn diverse motor behaviors simultaneously with a single policy network for quadruped locomotion. GALA significantly decreases the number of trainable parameters while producing appropriate motor behaviors by simply reactivating the generalist policy based on different sensory feedback and commands at run time. We experimentally analyze and demonstrate the versatile locomotion delivered by GALA on both simulated and real quadruped robots in various environments. The code is available at https://github.com/vsislab/GALA.

Stippling is a popular and fascinating sketching art in stylized illustrations. Various digital stippling techniques have been proposed to reduce tedious manual work. In this paper, we present a novel method to create high-quality color stippling from an input image in milliseconds. The key idea is to obtain stipples with predetermined incremental 2D sample sequences, which algorithms generate with sequential incrementality and distributional uniformity features. Two typical sequences are employed in our work: one is constructed from incremental Voronoi sets, and the other is from Poisson disk distributions. A threshold-based algorithm is then applied to determine stipple appearance and guarantee result quality. We extend color stippling with multitone level and radius adjustment to achieve improved visual quality. Detailed comparisons of the two sequences are conducted to explore further the strengths and weaknesses of the proposed method. For more information, please visit https://gitlab.com/maleiwhat/milliseconds-color-stippling.

The imperfect material effect is one of the most important themes to obtain photo-realistic results in rendering. Textile material rendering has always been a key area in the field of computer graphics. So far, a great deal of effort has been invested in its unique appearance and physicsbased simulation. The appearance of the dyeing effect commonly found in textiles has received little attention. This paper introduces techniques for simulation of staining effects on textiles. Pulling, wearing, squeezing, tearing, and breaking effects are more common imperfect effects of fabrics, these external forces will cause changes in the fabric structure, thus affecting the diffusion effect of stains. Based on the microstructure of yarn, we handle the effect of the stain on the imperfect textile surface. Our simulation results can achieve a photo-realistic effect.

Modeling virtual textiles has long been an appealing topic in computer graphics. To date, considerable effort has been devoted to their distinctive appearance and physically-based simulation. The apperance of staining patterns, commonly seen on textiles, has received comparatively little attention. This paper introduces techniques for simulating staining effects on fabric. Based on the microstructure of yarn, we propose a triple-layer model (TLM) to handle the liquid-yarn interaction for the wetting and wicking computation, and we formalize the liquid spreading in woven cloth into two typical actions, the in-yarn diffusion and the cross-yarn diffusion. The dye diffusion is driven by the liquid diffusion and the concentration distribution of pigments. The warp-weft anisotropy is handled by simulation of the yarn's structure in the two directions. Experimental results demonstrate that a wide range of fabric stain phenomenon on different textile materials, such as the water ring effect, the high saturate stain contour, and the dynamic wash away effect, can be simulated effectively without loss of visual realism. The realism of our simulation results is comparable to effects shown in photographs of real-world examples.

Abstract Illumination estimation is an essential problem in computer vision, graphics and augmented reality. In this paper, we propose a learning based method to recover low‐frequency scene illumination represented as spherical harmonic (SH) functions by pairwise photos from rear and front cameras on mobile devices. An end‐to‐end deep convolutional neural network (CNN) structure is designed to process images on symmetric views and predict SH coefficients. We introduce a novel Render Loss to improve the rendering quality of the predicted illumination. A high quality high dynamic range (HDR) panoramic image dataset was developed for training and evaluation. Experiments show that our model produces visually and quantitatively superior results compared to the state‐of‐the‐arts. Moreover, our method is practical for mobile‐based applications.

Abstract In this paper, we present a novel real‐time approach to generate high‐quality stippling on 3D scenes. The proposed method is built on a precomputed 2D sample sequence called incremental Voronoi set with blue‐noise properties. A rejection sampling scheme is then applied to achieve tone reproduction, by thresholding the sample indices proportional to the inverse target tonal value to produce a suitable stipple density. Our approach is suitable for stippling large‐scale or even dynamic scenes because the thresholding of individual stipples is trivially parallelizable. In addition, the static nature of the underlying sequence benefits the frame‐to‐frame coherence of the stippling. Finally, we propose an extension that supports stipples of varying sizes and tonal values, leading to smoother spatial and temporal transitions. Experimental results reveal that the temporal coherence and real‐time performance of our approach are superior to those of previous approaches.

In the setting of automated theorem proving, the output of an automated theorem prover is usually presented in text format, which is often too heavy to be understood. In the setting of model checking, it would be helpful if one can observe, at the same time, both the model structure under consideration and the verification procedure. To address these problems, a 3D visualization tool for modeling, demonstration and verification (VMDV for short) is proposed in this paper. The facilities of VMDV are illustrated by applying it to an automated theorem prover.

Multi-task learning has been proposed to improve the generalization performance by learning multiple tasks jointly. One challenge for this learning paradigm is to effectively seek the shared information across multiple tasks. In this paper, we propose a novel multi-task learning method to adaptively share information. Unlike many existing multi-task learning methods which impose strong assumptions on task related-ness, our method captures the relationships among tasks and identifies the disparities of each task simultaneously, thus can flexibly exploit the shared information. Moreover, we apply it to fine-grained categorization problem, which usually suffers from the difficulties of insufficient training data and high inter-class similarity. The experimental results on two widely used datasets show the superiority of our method compared with some state-of-the-art methods.

Solid textures exhibit several benefits over traditional texture mapping, such as no demanding for parameterization and providing internal information. However, the difficulty in accessing and high memory consumption seriously limit the usage of solid textures. We present an efficient approach to directly synthesize vector solid textures comprising 3D particles from 2D examples. Two-scale shaping model is introduced to automatically and accurately reconstruct 3D particle outlines from 2D cross sections. Low frequency spherical harmonics are used to morph smooth outlines while high frequency ones model particle surface details. These outlines are further converted to signed distance field grids for vector representation. Particle volume color is represented by radial basis functions. We arrange particles using simplified particle proxies to improve efficiency. Particles' position offsets are calculated according to the particle itself and one-ring neighbor particles' shapes iteratively. Finally, our cell-building algorithm constructs containers and computes scale for each particle instance. Experiments show that our algorithm can generate vector solid textures with plausible 3D particles.

Intrinsic image decomposition is a longstanding problem in computer vision. In this paper, we present a novel approach for efficiently decomposing an RGBD image into its reflectance and shading components. A robust super-pixel segmentation method is employed to select piece-wise constant reflectance regions and reduce the total number of unknowns. With the use of depth information, low frequency environment light can be represented by spherical harmonics and solved with super-pixels. After that, pixels that do not belong to any super-pixel are solved based on the super-pixels' shading. Compared to existing works, which often depend on the color Retinex assumption, our algorithm does not require any chromaticity-based constraints and enables us to solve many challenging cases such as color lighting environments and gray-scale textures. We also design an efficient solver for our system, and with our GPU implementation, it achieves 10-23 fps and boosts the decomposition process to real-time performance, enabling a wide range of applications such as dynamic object recoloring, re-texturing and virtual object composition.

We present an efficient interactive system for dressing a naked bird with feathers. In our system, a skeleton associated with guide feathers is used to describe the distribution of the body feathers. The special skeleton can be easily built by the user, given a 3D bird model as input. To address the problem of interpenetrations among feathers, the growth priority between the feather roots is defined, with which we obtain the growth order from a greedily constructed directed acyclic graph. Each feather is then adjusted in that order by a height field based collision resolution process. The height field not only provides an efficient way to detect the collision but also enables us to finely control the degree of collision during feather adjustments. The results show that our approach is capable of resolving the collisions among thousands of feathers in a few seconds. If model animation is desired, the feathers can be adjusted on the fly at interactive framerates. Details of our implementation are provided with several examples to demonstrate the effectiveness of our system.

In an animated scene, geometry and lighting often change in an unpredictable way. Rendering algorithms based on Monte Carlo methods are usually employed to precisely capture all features of an animated scene. However, Monte Carlo methods typically take a long time to produce a noise-free image. In this paper, we propose a variance reduction technique for Monte Carlo methods which exploits coherence between frames. Firstly, we introduce a dual cone model to measure the incident coherence intersecting camera rays in object space. Secondly, we allocate multiple frame buffers to store image samples from consecutive frames. Finally, the color of a pixel in one frame is computed by borrowing samples from neighboring pixels in current, previous, and subsequent frames. Our experiments show that noise is greatly reduced by our method since the number of effective samples is increased by use of borrowed samples.

ABSTRACT This paper presents a finite element method‐based framework for an object withering simulation modeled with heterogeneous material, such as fruits drying or decay. We introduce diffusion procedures for both the moisture content and decay spread, which are solved directly on a tetrahedral mesh representation of the fruit flesh. Then, we use the moisture content to control shrinkage through the initial strain, which is integrated into the Lagrangian dynamic equation, and solved with the finite element method. For the complex structure of the object, another fine triangle mesh is used to represent the skin, and its deformation is solved by a thin shell technique. To couple the motion between different layers of the fruit, a tracking force is used to pull the skin and drive its deformation together with the volume mesh. In comparison with the previous work, our method provides temporally and spatially varying parameters to model the complex phenomena of object withering. Moreover, the water diffusivity can also be given by user input to present various material properties of the cut section and skin‐covered area. Our algorithm is easy to implement and highly efficient in generating a realistic appearance for the withering effect. For a medium‐scale model, we can achieve interactive simulation. Copyright © 2012 John Wiley & Sons, Ltd.

Most of existing importance sampling methods for direct illumination exploit importance of illumination and surface BRDF. Without taking the visibility into consideration, they can not adaptively adjust the number of samples for each pixel during the sampling process. As a result, these methods tend to produce images with noise in partially occluded regions. In this paper, we introduce an incremental wavelet importance sampling approach, in which the visibility information is used to determine the number of samples at run time. For this purpose, we present a perceptual-based variance that is computed from visibility of samples. In the sampling process, the Halton sample points are incrementally warped for each pixel until the variance of warped samples converges. We demonstrate that our method is more efficient than existing importance sampling approaches.

We present a technique for interactive relighting in which source radiance, viewing direction, and BRDFs can all be changed on the fly. In handling dynamic BRDFs, our method efficiently accounts for the effects of BRDF modification on the reflectance and incident radiance at a surface point. For reflectance, we develop a BRDF tensor representation that can be factorized into adjustable terms for lighting, viewing, and BRDF parameters. For incident radiance, there exists a non-linear relationship between indirect lighting and BRDFs in a scene, which makes linear light transport frameworks such as PRT unsuitable. To overcome this problem, we introduceprecomputed transfer tensors(PTTs) which decompose indirect lighting into precomputable components that are each a function of BRDFs in the scene, and can be rapidly combined at run time to correctly determine incident radiance. We additionally describe a method for efficient handling of high-frequency specular reflections by separating them from the BRDF tensor representation and processing them using precomputed visibility information. With relighting based on PTTs, interactive performance with indirect lighting is demonstrated in applications to BRDF animation and material tuning.

Weathering modeling introduces blemishes such as dirt, rust, cracks and scratches to virtual scenery. In this paper we present a visual stimulation technique that works well for a wide variety of weathering phenomena. Our technique, called γ-ton tracing, is based on a type of aging-inducing particles called γ-tons. Modeling a weathering effect with γ-ton tracing involves tracing a large number of γ-tons through the scene in a way similar to photon tracing and then generating the weathering effect using the recorded γ-ton transport information. With this technique, we can produce weathering effects that are customized to the scene geometry and tailored to the weathering sources. Several effects that are challenging for existing techniques can be readily captured by γ-ton tracing. These include global transport effects. or "stainbleeding". γ-ton tracing also enables visual simulations of complex multi-weathering effects. Lastly γ-ton tracing can generate weathering effects that not only involve texture changes but also large-scale geometry changes. We demonstrate our technique with a variety of examples.

We propose a texture function for realistic modeling and efficient rendering of materials that exhibit surface mesostructures, translucency and volumetric texture variations. The appearance of such complex materials for dynamic lighting and viewing directions is expensive to calculate and requires an impractical amount of storage to precompute. To handle this problem, our method models an object as a shell layer, formed by texture synthesis of a volumetric material sample, and a homogeneous inner core. To facilitate computation of surface radiance from the shell layer, we introduce the shell texture function (STF) which describes voxel irradiance fields based on precomputed fine-level light interactions such as shadowing by surface mesostructures and scattering of photons inside the object. Together with a diffusion approximation of homogeneous inner core radiance, the STF leads to fast and detailed raytraced renderings of complex materials.

Abstract Realistic image synthesis of highly complex, natural scenes has been a challenging topic in computer graphics over the years. Generation of snowy scenery could be even more difficult due to the difficulty of using common modelling primitives such as polygons and curved surfaces to express the snow‐like shapes. In this paper, we propose a hybrid multi‐mapping method to tackle the snowy scenery problem, in which a displacement map is utilized to model snowy blocks on near objects based on proximate polygons, and a volumetric texture map is combined to handle distant objects such as bushes and trees. Our experimental results showed that the hybrid method is viable in producing realistic snowy scenery with comprehensive complex environments, and in a favourable requirement of storage usage and rendering computation. Copyright © 2003 John Wiley & Sons, Ltd.

We present a framework for knitwear modeling and rendering that accounts for characteristics that are particular to knitted fabrics. We first describe a model for animation that considers knitwear features and their effects on knitwear shape and interaction. With the computed free-form knitwear configurations, we present an efficient procedure for realistic synthesis based on the observation that a single cross section of yarn can serve as the basic primitive for modeling entire articles of knitwear. This primitive, called the lumislice, describes radiance from a yarn cross section that accounts for fine-level interactions among yarn fibers. By representing yarn as a sequence of identical but rotated cross sections, the lumislice can effectively propagate local microstructure over arbitrary stitch patterns and knitwear shapes. The lumislice accommodates varying levels of detail, allows for soft shadow generation, and capitalizes on hardware-assisted transparency blending. These modeling and rendering techniques together form a complete approach for generating realistic knitwear.

Human hair modeling is a difficult task. This paper presents a constructive hair modeling system with which users can sculpt a wide variety of hairstyles. Our Multiresolution Hair Modeling (MHM) system is based on the observed tendency of adjacent hair strands to form clusters at multiple scales due to static attraction. In our system, initial hair designs are quickly created with a small set of hair clusters. Refinements at finer levels are achieved by subdividing these initial hair clusters. Users can edit an evolving model at any level of detail, down to a single hair strand. High level editing tools support curling, scaling, and copy/paste, enabling users to rapidly create widely varying hairstyles. Editing ease and model realism are enhanced by efficient hair rendering, shading, antialiasing, and shadowing algorithms.

We present techniques for realistic modeling and rendering of feathers and birds. Our approach is motivated by the observation that a feather is a branching structure that can be described by an L-system. The parametric L-system we derived allows the user to easily create feathers of different types and shapes by changing a few parameters. The randomness in feather geometry is also incorporated into this L-system. To render a feather realistically, we have derived an efficient form of the bidirectional texture function (BTF), which describes the small but visible geometry details on the feather blade. A rendering algorithm combining the L-system and the BTF displays feathers photorealistically while capitalizing on graphics hardware for efficiency. Based on this framework of feather modeling and rendering, we developed a system that can automatically generate appropriate feathers to cover different parts of a bird's body from a few "key feathers" supplied by the user, and produce realistic renderings of the bird.

We present a method for efficient synthesis of photorealistic free-form knitwear. Our approach is motivated by the observation that a single cross-section of yarn can serve as the basic primitive for modeling entire articles of knitwear. This primitive, called the lumislice, describes radiance from a yarn cross-section based on fine-level interactions — such as occlusion, shadowing, and multiple scattering — among yarn fibers. By representing yarn as a sequence of identical but rotated cross-sections, the lumislice can effectively propagate local microstructure over arbitrary stitch patterns and knitwear shapes. This framework accommodates varying levels of detail and capitalizes on hardware-assisted transparency blending. To further enhance realism, a technique for generating soft shadows from yarn is also introduced.