c) (a) (b) Figure 1: Real-time rendering results with radiance regression functions for scenes with glossy interreflections (a), multiple local lights (b), and complex geometry and materials (c). AbstractWe present radiance regression functions for fast rendering of global illumination in scenes with dynamic local light sources. A radiance regression function (RRF) represents a non-linear mapping from local and contextual attributes of surface points, such as position, viewing direction, and lighting condition, to their indirect illumination values. The RRF is obtained from precomputed shading samples through regression analysis, which determines a function that best fits the shading data. For a given scene, the shading samples are precomputed by an offline renderer.The key idea behind our approach is to exploit the nonlinear coherence of the indirect illumination data to make the RRF both compact and fast to evaluate. We model the RRF as a multilayer acyclic feed-forward neural network, which provides a close functional approximation of the indirect illumination and can be efficiently evaluated at run time. To effectively model scenes with spatially variant material properties, we utilize an augmented set of attributes as input to the neural network RRF to reduce the amount of inference that the network needs to perform. To handle scenes with greater geometric complexity, we partition the input space of the RRF model and represent the subspaces with separate, smaller RRFs that can be evaluated more rapidly. As a result, the RRF model scales well to increasingly complex scene geometry and material variation. Because of its compactness and ease of evaluation, the RRF model enables real-time rendering with full global illumination effects, including changing caustics and multiple-bounce high-frequency glossy interreflections.

The appearance manifold [WTL * 06] is an efficient approach for modeling and editing time-variant appearance of materials from the BRDF data captured at single time instance. However, this method is difficult to apply in images in which weathering and shading variations are combined. In this paper, we present a technique for modeling and editing the weathering effects of an object in a single image with appearance manifolds. In our approach, we formulate the input image as the product of reflectance and illuminance. An iterative method is then developed to construct the appearance manifold in color space (i.e., Lab space) for modeling the reflectance variations caused by weathering. Based on the appearance manifold, we propose a statistical method to robustly decompose reflectance and illuminance for each pixel. For editing, we introduce a "pixel-walking" scheme to modify the pixel reflectance according to its position on the manifold, by which the detailed reflectance variations are well preserved. We illustrate our technique in various applications, including weathering transfer between two images that is first enabled by our technique. Results show that our technique can produce much better results than existing methods, especially for objects with complex geometry and shading effects.

Figure 1:Rendering results at 22 frames per-second of the Stanford Thai Statue (157 K triangles) with our system. AbstractWe present a real-time algorithm for rendering translucent objects of arbitrary shapes. We approximate the scattering of light inside the objects using the diffusion equation, which we solve on-the-fly using the GPU. Our algorithm is general enough to handle arbitrary geometry, heterogeneous materials, deformable objects and modifications of lighting, all in real-time. In a pre-processing step, we discretize the object into a regular 4-connected structure (QuadGraph). Due to its regular connectivity, this structure is easily packed into a texture and stored on the GPU. At runtime, we use the QuadGraph stored on the GPU to solve the diffusion equation, in real-time, taking into account the varying input conditions: Incoming light, object material and geometry. We handle deformable objects, provided the deformation does not change the topological structure of the objects.