3D Machine Learning Study & Practice

Notices

Important

These are the Reviews from 3D Machine Learning research papers, along with My Implementations of their models.

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Note

The papers are listed in the order I studied them, regardless of their publication year.

2025

■ DiffusionGS : Baking Gaussian Splatting into Diffusion Denosier for Fast and Scalable Single-Stage Image-to-3D Generation
  □ Paper Review & Code Practice (Updating)

■ 3DGS : 3D Gaussian Splatting for Real-Time Radiance Field Rendering (SIGGRAPH 2023)
  □ Paper Review & Code Practice

2023

■ DynIBaR : Neural Dynamic Image-Based Rendering (CVPR 2023)
  □ Paper Review

■ Mip-NeRF : A Multiscale Representation for Anti-Aliasing Neural Networks (CVPR 2021)
  □ Paper Review

■ PointMLP : Rethinking Network Design and Local Geometry in Point Cloud - A Simple Residual MLP Framework (ICLR 2022)
  □ Paper Review

■ Face-Vid2Vid : One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing (CVPR 2021)
  □ Paper Review
  □ Code Practice

■ Instant Neural Graphics Primitives with a Multiresolution Hash Encoding (SIGGRAPH 2022)
  □ Paper Review
  □ Code Practice

■ NeRF : Representing Scenes as Neural Radiance for View Synthesis (ECCV 2020)
  □ Paper Review
  □ Code Practice

■ PIFuHD : Multi-Level Pixel Aligned Implicit Function for High-Resolution 3D Human Digitization (CVPR 2020)
  □ Paper Review
  □ Code Practice

■ Text2Mesh : Text-Driven Neural Stylization for Meshes (CVPR 2022)
  □ Paper Review
  □ Code Practice