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ml-lab's Projects

icml-2015 icon icml-2015

Code for models in my ICML 2015 paper on VAEs, GSNs, etc.

icml-caffe icon icml-caffe

Implementation of ICML15 paper "Learning Transferable Features with Deep Adaptation Networks" based on caffe

icml17_knn icon icml17_knn

Deriving Neural Architectures from Sequence and Graph Kernels

icml2016 icon icml2016

Generative Adversarial Text-to-Image Synthesis

icml2016-minecraft icon icml2016-minecraft

Implementation of "Control of Memory, Active Perception, and Action in Minecraft"

icnet icon icnet

ICNet for Real-Time Semantic Segmentation on High-Resolution Images

idealize-lite-version icon idealize-lite-version

Idea Index Measurements with Shiny and R (Using compound Keyword Trend Strength, with Google Trends)

idnns icon idnns

explore DNNs via Infomration

if-net icon if-net

Implicit Feature Network (IF-Net) - Codebase

igan icon igan

iGAN: Interactive Image Generation powered by GAN

illustration2vec icon illustration2vec

A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.

im2im2im icon im2im2im

Composable unpaired image to image translation

im2latex-tensorflow icon im2latex-tensorflow

Tensorflow implementation of the HarvardNLP paper - What You Get Is What You See: A Visual Markup Decompiler (https://arxiv.org/pdf/1609.04938v1.pdf)

im2markup icon im2markup

Neural model for converting Image-to-Markup (by Yuntian Deng github.com/da03)

im2pencil icon im2pencil

The source code of CVPR19 'Im2Pencil: Controllable Pencil Illustration from Photographs'.

im2recipe icon im2recipe

Code supporting the CVPR 2017 paper "Learning Cross-modal Embeddings for Cooking Recipes and Food Images"

image-feature-detection-using-phase-stretch-transform icon image-feature-detection-using-phase-stretch-transform

PST or Phase Stretch Transform is an operator that finds features in an image. PST implemented using MATLAB here, takes an intensity image I as its input, and returns a binary image out of the same size as I, with 1's where the function finds sharp transitions in I and 0's elsewhere.

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