Learning Neural Light Transport

In recent years, deep generative models have gained significance due to their ability to synthesize natural-looking images with applications ranging from virtual reality to data augmentation for training computer vision models. While existing models are able to faithfully learn the image distribution of the training set, they often lack controllability as they operate in 2D pixel space and do not model the physical image formation process. In this work, we investigate the importance of 3D reasoning for photorealistic rendering. We present an approach for learning light transport in static and dynamic 3D scenes using a neural network with the goal of predicting photorealistic images. In contrast to existing approaches that operate in the 2D image domain, our approach reasons in both 3D and 2D space, thus enabling global illumination effects and manipulation of 3D scene geometry. Experimentally, we find that our model is able to produce photorealistic renderings of static and dynamic scenes. Moreover, it compares favorably to baselines which combine path tracing and image denoising at the same computational budget.Comment: 31 pages, 17 figure

Evaluating potential effects of solar power facilities on wildlife from an animal behavior perspective

Solar power is a renewable energy source with great potential to help meet increasing global energy demands and reduce our reliance on fossil fuels. However, research is scarce on how solar facilities affect wildlife. With input from professionals in ecology, conservation, and energy, we conducted a research-prioritization process and identified key questions needed to better understand impacts of solar facilities on wildlife. We focused on animal behavior, which can be used to identify population responses before mortality or other fitness consequences are documented. Behavioral studies can also offer approaches to understand the mechanisms leading to negative interactions (e.g., collision, singeing, avoidance) and provide insight into mitigating effects. Here, we review how behavioral responses to solar facilities, including perception, movement, habitat use, and interspecific interactions are priority research areas. Addressing these themes will lead to a more comprehensive understanding of the effects of solar power on wildlife and guide future mitigation

Evaluating potential effects of solar power facilities on wildlife from an animal behavior perspective

Solar power is a renewable energy source with great potential to helpmeet increasing global energy demands and reduce our reliance on fossilfuels. However, research is scarce on how solar facilities affect wildlife.With input from professionals in ecology, conservation, and energy, weconducted a research-prioritization process and identified key questionsneeded to better understand impacts of solar facilities on wildlife. Wefocused on animal behavior, which can be used to identify populationresponses before mortality or other fitness consequences aredocumented. Behavioral studies can also offer approaches to understandthe mechanisms leading to negative interactions (e.g., collision,singeing, avoidance) and provide insight into mitigating effects. Here, wereview how behavioral responses to solar facilities, including perception,movement, habitat use, and interspecific interactions are priorityresearch areas. Addressing these themes will lead to a morecomprehensive understanding of the effects of solar power on wildlifeand guide future mitigation