Introduction
- G-buffer Objaverse is rendered using the TIDE renderer on Objaverse with A10 for about 2000 GPU hours, yielding 30,000,000 images of Albedo, RGB, Depth, and Normal map. We proposed a rendering framework for high quality and high speed dataset rendering. The framework is a hybrid of rasterization and path tracing, the first ray-scene intersection is obtained by hardware rasterization and accurate indirect lighting by full hardware path tracing. Additionally, we using adaptive sampling, denoiser and path-guiding to further speed up the rendering time. In this rendering framework, we render 38 views of a centered object, including 24 views at elevation range from 5° to 30°, rotation = {r × 15° | r ∈ [0, 23]}, and 12 views at elevation from -5° to 5°, rotation = {r × 30° | r ∈ [0, 11]}, and 2 views for top and bottom respectively. In addition, we mannuly split the objaverse dataset into 10 general categories including Human-Shape, Animals, Daily-Used, Furnitures, Buildings&&Outdoor, Transportations, Plants, Food, Electronics and Poor-quality. + G-buffer Objaverse is rendered using the TIDE renderer on Objaverse with A10 for about 2000 GPU hours, yielding 30,000,000 images of Albedo, RGB, Depth, and Normal map. We proposed a rendering framework for high quality and high speed dataset rendering. The framework is a hybrid of rasterization and path tracing, the first ray-scene intersection is obtained by hardware rasterization and accurate indirect lighting by full hardware path tracing. Additionally, we using adaptive sampling, denoiser and path-guiding to further speed up the rendering time. In this rendering framework, we render 38 views of a centered object, including 24 views at elevation range from 5° to 30°, rotation = {r × 15° | r ∈ [0, 23]}, and 12 views at elevation from -5° to 5°, rotation = {r × 30° | r ∈ [0, 11]}, and 2 views for top and bottom respectively. In addition, we mannuly split about 300,000 of the objaverse dataset into 10 general categories including Human-Shape, Animals, Daily-Used, Furnitures, Buildings&&Outdoor, Transportations, Plants, Food, Electronics and Poor-quality.
