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         <h2 class="title is-3">Introduction</h2>
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-            G-buffer Objaverse is rendered using the <a href="https://developer.aliyun.com/article/784784?spm=a2c6h.14164896.0.0.d7c247c5q1Pb9G&scm=20140722.S_community@@%E6%96%87%E7%AB%A0@@784784._.ID_784784-RL_tidejs-LOC_search~UND~community~UND~item-OR_ser-V_3-P0_0" target="_blank" style="color: rgb(47, 141, 255);">TIDE </a> 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 <a href="https://developer.aliyun.com/article/784784?spm=a2c6h.14164896.0.0.d7c247c5q1Pb9G&scm=20140722.S_community@@%E6%96%87%E7%AB%A0@@784784._.ID_784784-RL_tidejs-LOC_search~UND~community~UND~item-OR_ser-V_3-P0_0" target="_blank" style="color: rgb(47, 141, 255);">TIDE </a> 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.
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           <img src="static/images/intro.png" alt="MY ALT TEXT"/>
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