Low rank solvers #################################### benchmark/ : folder with the random instances used in the paper. #################################### code/ : folder that contains the code. Usage : ./mixing INPUT_INSTANCE OPTIONS OPTIONS : solver : "1" for LR-LAS "2" for LR-BCD rank : "-1" for running with rank r = ceil(sqrt(2n)) "k" for running with rank r = k rounding : "k" for computing the best integer solution value with k rounding schemes example : ./mixing ../benchmark/rd50-3-sparse-0.wcsp 1 -1 50 OUTPUT : [Upper bound value] [lower bound value] [cpu time] [Best upper bound value after rounding schemes] [cpu time rounding schemes] Eigen3 must be installed and the path to eigen3 must be updated in the makefile.
Efficient semidefinite bounds for multi-label discrete graphical models.
Overview
A repository that shares tuning results of trained models generated by TensorFlow / Keras. Post-training quantization (Weight Quantization, Integer Quantization, Full Integer Quantization, Float16 Quantization), Quantization-aware training. TensorFlow Lite. OpenVINO. CoreML. TensorFlow.js. TF-TRT. MediaPipe. ONNX. [.tflite,.h5,.pb,saved_model,tfjs,tftrt,mlmodel,.xml/.bin, .onnx]
PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar
Implementation for our ICCV 2021 paper: Dual-Camera Super-Resolution with Aligned Attention Modules
DCSR: Dual Camera Super-Resolution Implementation for our ICCV 2021 oral paper: Dual-Camera Super-Resolution with Aligned Attention Modules paper | pr
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
OpenCVのGrabCut()を利用したセマンティックセグメンテーション向けアノテーションツール(Annotation tool using GrabCut() of OpenCV. It can be used to create datasets for semantic segmentation.)
[Japanese/English] GrabCut-Annotation-Tool GrabCut-Annotation-Tool.mp4 OpenCVのGrabCut()を利用したアノテーションツールです。 セマンティックセグメンテーション向けのデータセット作成にご使用いただけます。 ※Grab
DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021)
DPT This repo is the official implementation of DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021). We provide code and model
Torchreid: Deep learning person re-identification in PyTorch.
Torchreid Torchreid is a library for deep-learning person re-identification, written in PyTorch. It features: multi-GPU training support both image- a
Minimisation of a negative log likelihood fit to extract the lifetime of the D^0 meson (MNLL2ELDM)
Minimisation of a negative log likelihood fit to extract the lifetime of the D^0 meson (MNLL2ELDM) Introduction The average lifetime of the $D^{0}$ me
Just Go with the Flow: Self-Supervised Scene Flow Estimation
Just Go with the Flow: Self-Supervised Scene Flow Estimation Code release for the paper Just Go with the Flow: Self-Supervised Scene Flow Estimation,
Powerful unsupervised domain adaptation method for dense retrieval.
Powerful unsupervised domain adaptation method for dense retrieval
Semantic Segmentation with SegFormer on Drone Dataset.
SegFormer_Segmentation Semantic Segmentation with SegFormer on Drone Dataset. You can check out the blog on Medium You can also try out the model with
Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fusion Framework via Self-Supervised Multi-Task Learning. Code will be available soon.
Official-PyTorch-Implementation-of-TransMEF Official PyTorch implementation of our AAAI22 paper: TransMEF: A Transformer-Based Multi-Exposure Image Fu
LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021
LTR_CrossEncoder: Legal Text Retrieval Zalo AI Challenge 2021 We propose a cross encoder model (LTR_CrossEncoder) for information retrieval, re-retrie
PyTorch implementation of spectral graph ConvNets, NIPS’16
Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson
Official implementation for "Image Quality Assessment using Contrastive Learning"
Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi
basic tutorial on pytorch
Quick Tutorial on PyTorch PyTorch Basics Linear Regression Logistic Regression Artificial Neural Networks Convolutional Neural Networks Recurrent Neur
Object detection on multiple datasets with an automatically learned unified label space.
Simple multi-dataset detection An object detector trained on multiple large-scale datasets with a unified label space; Winning solution of E
The code for paper Efficiently Solve the Max-cut Problem via a Quantum Qubit Rotation Algorithm
Quantum Qubit Rotation Algorithm Single qubit rotation gates $$ U(\Theta)=\bigotimes_{i=1}^n R_x (\phi_i) $$ QQRA for the max-cut problem This code wa
Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)
Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P
source code and pre-trained/fine-tuned checkpoint for NAACL 2021 paper LightningDOT
LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval This repository contains source code and pre-trained/fine-tun