chenxi840221,github

3d-convolutional-autoencoder-for-fmri-volumes

Learning spatial and temporal features of fMRI brain images.

3d-mri-brain-tumor-segmentation-using-autoencoder-regularization

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

3d-r2n2

Single/multi view image(s) to voxel reconstruction using a recurrent neural network

3ddepthwiseseparablenetworkforlightfield

3dgnn_pytorch

3D Graph Neural Networks for RGBD Semantic Segmentation

adabound

An optimizer that trains as fast as Adam and as good as SGD.

advent

Adversarial Entropy Minimization for Domain Adaptation in Semantic Segmentation

antialiased-cnns

Antialiasing cnns to improve stability and accuracy. In ICML 2019.

apex

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

appearance-flow

A deep learning framework for synthesizing novel views of objects and scenes

attention-cnn

Source code for "On the Relationship between Self-Attention and Convolutional Layers"

blender-addon

Blender Addon to render light fields with depth and disparity maps

brats18-project

Brain tumor segmentation using fully-convolutional deep neural networks.

bts

From Big to Small: Multi-Scale Local Planar Guidance for Monocular Depth Estimation

calibnet

Self-Supervised Extrinsic Calibration using 3D Spatial Transformer Networks

cbmv

Welcome to the code repository of CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation. CVPR 2018

This repository contains the source code for the semantic image segmentation method described in the ICCV 2015 paper: Conditional Random Fields as Recurrent Neural Networks. http://crfasrnn.torr.vision/