3D生成四大核心范式对比 - Comparison View
COLUMN 1 - 体素/栅格 (Voxel/Grid):
- 核心表示: 规则3D网格,每个体素存储占据值
- 代表方法: 3D-GAN, OGN, Shape-E
- 优势: 结构简单,卷积操作成熟,易于与2D架构对接
- 局限: 分辨率立方增长O(N³),内存瓶颈(64³上限),表面粗糙
COLUMN 2 - 点云/结构 (Point Cloud):
- 核心表示: N个3D坐标点,无拓扑连接
- 代表方法: PointFlow, ShapeGF, Point-E
- 优势: 灵活紧凑,天然非结构化,可直接从传感器获取
- 局限: 缺乏拓扑和表面,渲染需后处理,无序性
COLUMN 3 - 隐式场/神经场 (Implicit/Neural Field):
- 核心表示: 连续函数f:R³→R(密度/SDF),MLP参数化
- 代表方法: NeRF, DreamFusion, 3DGS, ProlificDreamer
- 优势: 无限分辨率,无拓扑限制,照片级真实
- 局限: 训练慢(NeRF)或存储大(3DGS),提取网格需MC
COLUMN 4 - 可微表面积 (Differentiable Surface):
- 核心表示: 显式三角网格+可微光栅化
- 代表方法: DIB-R, GET3D
- 优势: 直接输出可用网格,高效渲染,与引擎兼容
- 局限: 拓扑固定,需要隐式场辅助
BOTTOM: 当前主流 = 隐式场/神经场(尤其SDS路线)
Flat vector comparison with four-column layout. Clear visual separation. PALETTE: macaron — soft pastel color blocks COLORS: Warm Cream background (#F5F0E8), each column in distinct macaron tone (Blue #A8D8EA, Mint #B5E5CF, Lavender #D5C6E0, Peach #FFD5C2), Coral Red (#E8655A) for emphasis on limitations, Mustard Yellow (#F2CC8F) for key method names ELEMENTS: Column headers with representative 3D shape icon, black outlines, bullet lists, bottom highlight bar ASPECT: 16:9
Clean composition with generous white space. Simple or no background. Main elements centered or positioned by content needs. Color values (#hex) and color names are rendering guidance only — do NOT display color names, hex codes, or palette labels as visible text in the image. Text should be large and prominent with handwritten-style fonts. Keep minimal, focus on keywords. Language: Chinese.