Abstract Differentiable rendering (DR) enables various computer graphics and computer vision applications through gradient‐based optimization with derivatives of the rendering equation. Most rasterization‐based approaches are built on general‐purpose automatic differentiation (AD) libraries and DR‐specific modules handcrafted using CUDA. Such a system design mixes DR algorithm implementation and algorithm building blocks, resulting in hardware dependency and limited performance. In this paper, we present a practical hardware‐agnostic differentiable renderer called Dressi, which is based on a new full AD design. The DR algorithms of Dressi are fully written in our Vulkan‐based AD for DR, Dressi‐AD, which supports all primitive operations for DR. Dressi‐AD and our inverse UV technique inside it bring hardware independence and acceleration by graphics hardware. Stage packing, our runtime optimization technique, can adapt hardware constraints and efficiently execute complex computational graphs of DR with reactive cache considering the render pass hierarchy of Vulkan. HardSoftRas, our novel rendering process, is designed for inverse rendering with a graphics pipeline. Under the limited functionalities of the graphics pipeline, HardSoftRas can propagate the gradients of pixels from the screen space to far‐range triangle attributes. Our experiments and applications demonstrate that Dressi establishes hardware independence, high‐quality and robust optimization with fast speed, and photorealistic rendering.

Efficient global illumination computation in dynamically changing environments is an important practical problem. In high-quality animation rendering costly "final gathering" technique is commonly used. We extend this technique into temporal domain by exploiting coherence between the subsequent frames. For this purpose we store previously computed incoming radiance samples and refresh them evenly in space and time using some aging criteria. The approach is based upon a two-pass photon mapping algorithm with irradiance cache, but it can be applied also in other gathering methods. The algorithm significantly reduces the cost of expensive indirect lighting computation and suppresses temporal aliasing with respect to the state of the art frame-by-frame rendering techniques

We present a method for efficient global illumination computation in dynamic environments by taking advantage of temporal coherence of lighting distribution. The method is embedded in the framework of stochastic photon tracing and density estimation techniques. A locally operating energy-based error metric is used to prevent photon processing in the temporal domain for the scene regions in which lighting distribution changes rapidly. A perception-based error metric suitable for animation is used to keep noise inherent in stochastic methods below the sensitivity level of the human observer. As a result a perceptually-consistent quality across all animation frames is obtained. Furthermore, the computation cost is reduced compared to the traditional approaches operating solely in the spatial domain.

We consider accelerated rendering of high quality walkthrough animation sequences along predefined paths. To improve rendering performance, we use a combination of a hybrid ray tracing and image-based rendering (IBR) technique and a novel perception-based antialiasing technique. In our rendering solution, we derive as many pixels as possible using inexpensive IBR techniques without affecting the animation quality. A perception-based spatiotemporal animation quality metric (AQM) is used to automatically guide such a hybrid rendering. The image flow (IF) obtained as a byproduct of the IBR computation is an integral part of the AQM. The final animation quality is enhanced by an efficient spatiotemporal antialiasing which utilizes the IF to perform a motion-compensated filtering. The filter parameters have been tuned using the AQM predictions of animation quality as perceived by the human observer. These parameters adapt locally to the visual pattern velocity.