Posts by Tags

3D

Faster Neural Radiance Fields Inference

The Neural Radiance Fields (NeRF) proposed an interesting way to represent a 3D scene using an implicit network for high fidelity volumetric rendering. Compa...

3D Convolutional Neural Network

3D Features

3D Perception

3D Reconstruction

3D semantic segmentation

3D vision

4D convolutional neural network

Blog

Switching to Visual Studio Code

I’ve been using VIM for most of my Ph.D. years and one of the reasons why I stick with VIM is that I could just ssh to a remote server and recover environmen...

Classification

Data Processing Inequality

Dirichlet Process

Documentation

Switching to Visual Studio Code

I’ve been using VIM for most of my Ph.D. years and one of the reasons why I stick with VIM is that I could just ssh to a remote server and recover environmen...

Expectation Maximization

Extension

Pytorch Extension with a Makefile

Pytorch is a great neural network library that has both flexibility and power. Personally, I think it is the best neural network library for prototyping (adv...

Free Form Deformation

Gaussian Process

Learning Gaussian Process Covariances

A Gaussian process is a non-parametric model which can represent a complex function using a growing set of data. Unlike a neural network, which can also lear...

Gaussian Process Regression

Generative Adversarial Network

Geometric Pattern Recognition

Global Registration

Google Protocol Buffer

High-dimensional Convolutional Networks

IDE

Switching to Visual Studio Code

I’ve been using VIM for most of my Ph.D. years and one of the reasons why I stick with VIM is that I could just ssh to a remote server and recover environmen...

Information Theory

Instance Segmentation

Inverse Reinforcement Learning

Loss

Matrix Calculus

Memory

Neural Networks

Neural Radiance Fields

Neuroscience

Nonparametric Bayesian

Object manipulation

Pytorch

Pytorch Extension with a Makefile

Pytorch is a great neural network library that has both flexibility and power. Personally, I think it is the best neural network library for prototyping (adv...

Regression

Representation Learning

Semantic Correspondence

Variational Inference

Wasserstein distance

Weakly supervised learning

back propagation

barycentric coordinate

caffe

Making a Caffe Layer

Caffe is one of the most popular open-source neural network frameworks. It is modular, clean, and fast. Extending it is tricky but not as difficult as extend...

correspondence

Universal Correspondence Network

TL;DR: Universal Correspondence Network proposed the first fully convolutional way to learn contrastive embeddings for correspondences.

f-divergence

fully convolutional neural network

Universal Correspondence Network

TL;DR: Universal Correspondence Network proposed the first fully convolutional way to learn contrastive embeddings for correspondences.

graphics

Faster Neural Radiance Fields Inference

The Neural Radiance Fields (NeRF) proposed an interesting way to represent a 3D scene using an implicit network for high fidelity volumetric rendering. Compa...

matrix norm

mesh

multi view

neural network

Faster Neural Radiance Fields Inference

The Neural Radiance Fields (NeRF) proposed an interesting way to represent a 3D scene using an implicit network for high fidelity volumetric rendering. Compa...

Universal Correspondence Network

TL;DR: Universal Correspondence Network proposed the first fully convolutional way to learn contrastive embeddings for correspondences.

point cloud

prediction

programming

Setting Class Attributes in Python

Setting class attributes in python can be tedious. In this post, I want to summarize a trick that I’ve been using to simplify this process.

python

Setting Class Attributes in Python

Setting class attributes in python can be tedious. In this post, I want to summarize a trick that I’ve been using to simplify this process.

reconstruction

recurrent neural network

rendering

Faster Neural Radiance Fields Inference

The Neural Radiance Fields (NeRF) proposed an interesting way to represent a 3D scene using an implicit network for high fidelity volumetric rendering. Compa...

scene graph

single view

spatio-temporal perception

universal correspondence network

Universal Correspondence Network

TL;DR: Universal Correspondence Network proposed the first fully convolutional way to learn contrastive embeddings for correspondences.