shubhampachori12110095 Goto Github PK
Name: Shubham Pachori
Type: User
Bio: Learning to extract signal from noise.
Location: Somewhere in India
Name: Shubham Pachori
Type: User
Bio: Learning to extract signal from noise.
Location: Somewhere in India
Learning to Evaluate Image Captioning. CVPR 2018
Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning. CVPR 2018
Recovering Realistic Texture in Image Super-resolution by Deep Spatial Feature Transform (CVPR 2018) http://mmlab.ie.cuhk.edu.hk/projects/SFTGAN/
Code for 2nd Place Solution in Face Anti-spoofing Attack Detection Challenge @ CVPR2019
Learning Deep Representations of Fine-grained Visual Descriptions
Code for our CVPR 2016 paper on Fashion styles in 128 floats.
CVPR'17 GAN Tutorial
Context Encoding for Semantic Segmentation MegaDepth: Learning Single-View Depth Prediction from Internet Photos LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume On the Robustness of Semantic Segmentation Models to Adversarial Attacks SPLATNet: Sparse Lattice Networks for Point Cloud Processing Left-Right Comparative Recurrent Model for Stereo Matching Enhancing the Spatial Resolution of Stereo Images using a Parallax Prior Unsupervised CCA Discovering Point Lights with Intensity Distance Fields CBMV: A Coalesced Bidirectional Matching Volume for Disparity Estimation Learning a Discriminative Feature Network for Semantic Segmentation Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation Unsupervised Deep Generative Adversarial Hashing Network Monocular Relative Depth Perception with Web Stereo Data Supervision Single Image Reflection Separation with Perceptual Losses Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains EPINET: A Fully-Convolutional Neural Network for Light Field Depth Estimation by Using Epipolar Geometry FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds Decorrelated Batch Normalization Unsupervised Learning of Depth and Egomotion from Monocular Video Using 3D Geometric Constraints PU-Net: Point Cloud Upsampling Network Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer Tell Me Where To Look: Guided Attention Inference Network Residual Dense Network for Image Super-Resolution Reflection Removal for Large-Scale 3D Point Clouds PlaneNet: Piece-wise Planar Reconstruction from a Single RGB Image Fully Convolutional Adaptation Networks for Semantic Segmentation CRRN: Multi-Scale Guided Concurrent Reflection Removal Network DenseASPP: Densely Connected Networks for Semantic Segmentation SGAN: An Alternative Training of Generative Adversarial Networks Multi-Agent Diverse Generative Adversarial Networks Robust Depth Estimation from Auto Bracketed Images AdaDepth: Unsupervised Content Congruent Adaptation for Depth Estimation DeepMVS: Learning Multi-View Stereopsis GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose GeoNet: Geometric Neural Network for Joint Depth and Surface Normal Estimation Single-Image Depth Estimation Based on Fourier Domain Analysis Single View Stereo Matching Pyramid Stereo Matching Network A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation Image Correction via Deep Reciprocating HDR Transformation Occlusion Aware Unsupervised Learning of Optical Flow PAD-Net: Multi-Tasks Guided Prediciton-and-Distillation Network for Simultaneous Depth Estimation and Scene Parsing Surface Networks Structured Attention Guided Convolutional Neural Fields for Monocular Depth Estimation TextureGAN: Controlling Deep Image Synthesis with Texture Patches Aperture Supervision for Monocular Depth Estimation Two-Stream Convolutional Networks for Dynamic Texture Synthesis Unsupervised Learning of Single View Depth Estimation and Visual Odometry with Deep Feature Reconstruction Left/Right Asymmetric Layer Skippable Networks Learning to See in the Dark
This repository contains algorithms in C++ to solve the Capacitated Vehicle Routing Problem (cvrp).
Practical implementation of Constrained Vehicle Routing Problem.
Capacitated Vehicle Routing Problem solved with Ant Colony Optimization
A simple capacitated vehicle routing problem using Gurobi
Comparison of an RL-based approach with more traditional Combinatorial Optimizations techniques to solve the CVRP
Capacitated Vehicle Routing Problem solved with Ant Colony Optimization
capacitated vehicle routing problem with time windows
Capacitated Vehicle Routing Problem with Time Windows (NP-Hard). Winner at ICHack 18.
Capacitated vehicle routing with time windows (CVRPTW) optimization
Solving a Capacitated Vehicle Routing Problem with time windows constraints (CVRPTW) with Mixed Integer Linear Programming (MILP) in python-gurobi API.
Your not so typical resume parser
Source code for paper Classification with Costly Features using Deep Reinforcement Learning.
Author implementation of "Contextualized Word Representations for Reading Comprehension" (Salant et al. 2017)
Source codes for paper "Neural Networks Incorporating Dictionaries for Chinese Word Segmentation", AAAI 2018
ACL2015_code_Gated Recursive Neural Network for Chinese Word Segmentation
EMNLP2015_code_Long Short-Term Memory Neural Networks for Chinese Word Segmentation
Causal Explanations (CXPlain) is a method for explaining the predictions of any machine-learning model.
Code to accompany ICML 2018 paper
Reimplementation of cycle-gan(https://arxiv.org/pdf/1703.10593.pdf) with improved w-gan(https://arxiv.org/abs/1704.00028) loss in tensorflow.
Tensorflow implementation of CycleGAN
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.