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3dgan-release

3D Generative Adversarial Network

assignment4

First few implementation of filters

awesome-computer-vision

A curated list of awesome computer vision resources

awsome-domain-adaptation

A collection of AWESOME things about domian adaptation

bcdu-net

BCDU-Net : Medical Image Segmentation

boundary-loss

Official code for "Boundary loss for highly unbalanced segmentation", runner-up for best paper award at MIDL 2019. Extended version in MedIA, volume 67, January 2021.

cf

Removing Confounding Factors Associated Weights in Deep Neural Networks Improves the Prediction Accuracy for Healthcare Applications

clusterpost

Post jobs to a computing grid and store the results in a couch database local or remote

colonvisualization

This project focus on visualization of quasi-tubular objects and the deformation driven by centerline

condensa

Programmable Model Compression

conformalizedmcf

Conformalized Mean Curvature Flow

contentdisentanglement

PyTorch implementation of "Emerging Disentanglement in Auto-Encoder Based Unsupervised Image Content Transfer"

da

Unsupervised Domain Adaptation Papers and Code

deep-image-analogy-pytorch

A python implementation of Deep-Image-Analogy based on pytorch.

deeplab2

DeepLab2 is a TensorFlow library for deep labeling, aiming to provide a unified and state-of-the-art TensorFlow codebase for dense pixel labeling tasks.

deepsdf

Learning Continuous Signed Distance Functions for Shape Representation

dextr-pytorch

Deep Extreme Cut http://www.vision.ee.ethz.ch/~cvlsegmentation/dextr

domainintersectiondifference

Pytorch implementation of of "Domain Intersection and Domain Difference" (ICCV 2019)

examples

fastestimator

building deep learning model fast & easy

fastpd

The shared library generator for Nikos Komodakis's FastPD MRF optimization library

flownet2-pytorch

Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks

focal-tversky-unet

This repo contains the code for our paper "A novel focal Tversky loss function and improved Attention U-Net for lesion segmentation" accepted at IEEE ISBI 2019.

grader

Grading framework for COMP 110

grokking-the-coding-interview-patterns

This course categorizes coding interview problems into a set of 16 patterns. Each pattern will be a complete tool - consisting of data structures, algorithms, and analysis techniques - to solve a specific category of problems. The goal is to develop an understanding of the underlying pattern, so that, we can apply that pattern to solve other problems.

groupwisethinshelldemons

keras-applications

Reference implementations of popular deep learning models.

ksrt

libigl-example-project

A blank project example showing how to use libigl and cmake.

long_matlab

matlab code of thickness analysis