screnary

3D-Free-Form-Deformation

Final project for Data-Visualization(DATA130012) in Fudan University.

Algorithm_python

my algorithm exercises using python

blender_shapenet_render

using blender and python to render 3D Shapes from ShapeNet

CGIntrinsics

This is the CGIntrinsics implementation described in the paper "CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering, Z. Li and N. Snavely, ECCV 2018".

GL_learning

using opengl to render 3D meshes, using python + pyopengl

IntrinsicDataRefinement

Matlab code for data refinement of the MPI data for intrinsic decomposition.

Mesh2Points

Convert 3D mesh model to point clouds using Virtual Scanner and Furthest Point Sampling.

Shapenet_Class_Analysis

analysis dataset for fine-grained classification

SingleImageIntrinsic

Single Image Intrinsic Decomposition with Discriminative Feature Encoding

VoxSegNet

screnary/SingleImageIntrinsic

Single Image Intrinsic Decomposition with Discriminative Feature Encoding

screnary/VoxSegNet

screnary/IntrinsicDataRefinement

Matlab code for data refinement of the MPI data for intrinsic decomposition.

screnary/Shapenet_Class_Analysis

analysis dataset for fine-grained classification

screnary/CGIntrinsics

This is the CGIntrinsics implementation described in the paper "CGIntrinsics: Better Intrinsic Image Decomposition through Physically-Based Rendering, Z. Li and N. Snavely, ECCV 2018".

screnary/3D-Free-Form-Deformation

Final project for Data-Visualization(DATA130012) in Fudan University.

screnary/Algorithm_python

my algorithm exercises using python

screnary/blender_shapenet_render

using blender and python to render 3D Shapes from ShapeNet

screnary/GL_learning

using opengl to render 3D meshes, using python + pyopengl

screnary/Mesh2Points

Convert 3D mesh model to point clouds using Virtual Scanner and Furthest Point Sampling.

screnary/3D-Machine-Learning

A resource repository for 3D machine learning

screnary/alphafold

Open source code for AlphaFold.

screnary/apng2gif-mac

ffmpeg shell

screnary/Depth-Anything-V2

Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation

screnary/Earth-vue-cesium-with-plugin

screnary/Earth_Cesium_Vue

using Cesium + Vue to learn digital earth

screnary/FlowErrorViz

screnary/Free-Form-Deformation

Free Form Deformation Sederberg's technique F

screnary/gaussian-splatting

Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"

screnary/google-research

Google Research-SNERG

screnary/instagan

PyTorch implementation of "InstaGAN: Instance-aware Image Translation" (ICLR 2019)

screnary/Intrinsic_video_project

screnary/IntrinsicImage

Implementation codes of CVPR 2018 Oral paper "Revisiting Deep Intrinsic Image Decompositions"

screnary/lucent

Lucid library adapted for PyTorch

screnary/lucid

A collection of infrastructure and tools for research in neural network interpretability.

screnary/modelscope

ModelScope: bring the notion of Model-as-a-Service to life.

screnary/Seg3D

Auto Segmentation GUI using PyQT/PySide2

screnary/shoufaMRI

MRIdataProcessing

screnary/state-of-the-art-result-for-machine-learning-problems

This repository provides state of the art (SoTA) results for all machine learning problems. We do our best to keep this repository up to date. If you do find a problem's SoTA result is out of date or missing, please raise this as an issue or submit Google form (with this information: research paper name, dataset, metric, source code and year). We will fix it immediately.

screnary/template_ffd

Code for paper "Learning Free-Form Deformations for 3D Object Reconstruction"