Abstract Texture‐space shading (TSS) methods decouple shading and rasterization, allowing shading to be performed at a different framerate and spatial resolution than rasterization. TSS has many potential applications, including streaming shading across networks, and reducing rendering cost via shading reuse across consecutive frames and/or shading at reduced resolutions relative to display resolution. Real‐time TSS shading requires texture atlases small enough to be easily stored in GPU memory. Using static atlases leads to significant space wastage, motivating real‐time per‐frame atlassing strategies that pack only the content visible in each frame. We propose FastAtlas, a novel atlasing method that runs entirely on the GPU and is fast enough to be performed at interactive rates per‐frame. Our method combines new per‐frame chart computation and parametrization strategies and an efficient general chart packing algorithm. Our chartification strategy removes visible seams in output renders, and our parameterization ensures a constant texel‐to‐pixel ratio, avoiding undesirable undersampling artifacts. Our packing method is more general, and produces more tightly packed atlases, than previous work. Jointly, these innovations enable us to produce shading outputs of significantly higher visual quality than those produced using alternative atlasing strategies. We validate FastAtlas by shading and rendering challenging scenes using different atlasing settings, reflecting the needs of different TSS applications (temporal reuse, streaming, reduced or elevated shading rates). We extensively compare FastAtlas to prior alternatives and demonstrate that it achieves better shading quality and reduces texture stretch compared to prior approaches using the same settings.

Abstract Interactive global illumination remains a challenge in radiometrically and geometrically complex scenes. Specialized sampling strategies are effective for specular and near‐specular transport because the scattering has relatively low directional variance per scattering event. In contrast, the high variance from transport paths comprising multiple rough glossy or diffuse scattering events remains notoriously difficult to resolve with a small number of samples. We extend unidirectional path tracing to address this by combining screen‐space reservoir resampling and sparse world‐space probes, significantly improving sample efficiency for transport contributions that terminate on diffuse scattering events. Our experiments demonstrate a clear improvement—at equal time and equal quality—over purely path traced and purely probe‐based baselines. Moreover, when combined with commodity denoisers, we are able to interactively render global illumination in complex scenes.

We present a networked, high-performance graphics system that combines dynamic, high-quality, ray traced global illumination computed on a server with direct illumination and primary visibility computed on a client. This approach provides many of the image quality benefits of real-time ray tracing on low-power and legacy hardware, while maintaining a low latency response and mobile form factor.

Quality, diversity, and size of training data are critical factors for learning-based gaze estimators. We create two datasets satisfying these criteria for near-eye gaze estimation under infrared illumination: a synthetic dataset using anatomically-informed eye and face models with variations in face shape, gaze direction, pupil and iris, skin tone, and external conditions (2M images at 1280x960), and a real-world dataset collected with 35 subjects (2.5M images at 640x480). Using these datasets we train neural networks performing with sub-millisecond latency. Our gaze estimation network achieves 2.06(±0.44)° of accuracy across a wide 30°×40° field of view on real subjects excluded from training and 0.5° best-case accuracy (across the same FOV) when explicitly trained for one real subject. We also train a pupil localization network which achieves higher robustness than previous methods.

We present a near-eye augmented reality display with resolution and focal depth dynamically driven by gaze tracking. The display combines a traveling microdisplay relayed off a concave half-mirror magnifier for the high-resolution foveal region, with a wide field-of-view peripheral display using a projector-based Maxwellian-view display whose nodal point is translated to follow the viewer's pupil during eye movements using a traveling holographic optical element. The same optics relay an image of the eye to an infrared camera used for gaze tracking, which in turn drives the foveal display location and peripheral nodal point. Our display supports accommodation cues by varying the focal depth of the microdisplay in the foveal region, and by rendering simulated defocus on the "always in focus" scanning laser projector used for peripheral display. The resulting family of displays significantly improves on the field-of-view, resolution, and form-factor tradeoff present in previous augmented reality designs. We show prototypes supporting 30, 40 and 60 cpd foveal resolution at a net 85° × 78° field of view per eye.