382 Repositories
Python entity-resolution Libraries
Image Super-Resolution by Neural Texture Transfer
SRNTT: Image Super-Resolution by Neural Texture Transfer Tensorflow implementation of the paper Image Super-Resolution by Neural Texture Transfer acce
PyTorch code for our paper "Gated Multiple Feedback Network for Image Super-Resolution" (BMVC2019)
Gated Multiple Feedback Network for Image Super-Resolution This repository contains the PyTorch implementation for the proposed GMFN [arXiv]. The fram
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade
Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" (NeurIPS'20)
IGNN Code repo for "Cross-Scale Internal Graph Neural Network for Image Super-Resolution" [paper] [supp] Prepare datasets 1 Download training dataset
Second-order Attention Network for Single Image Super-resolution (CVPR-2019)
Second-order Attention Network for Single Image Super-resolution (CVPR-2019) "Second-order Attention Network for Single Image Super-resolution" is pub
Torch code for our CVPR 2018 paper "Residual Dense Network for Image Super-Resolution" (Spotlight)
Residual Dense Network for Image Super-Resolution This repository is for RDN introduced in the following paper Yulun Zhang, Yapeng Tian, Yu Kong, Bine
ECCV18 Workshops - Enhanced SRGAN. Champion PIRM Challenge on Perceptual Super-Resolution. The training codes are in BasicSR.
ESRGAN (Enhanced SRGAN) [ 🚀 BasicSR] [Real-ESRGAN] ✨ New Updates. We have extended ESRGAN to Real-ESRGAN, which is a more practical algorithm for rea
A cross-document event and entity coreference resolution system, trained and evaluated on the ECB+ corpus.
A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution. Introduction This repo contains experimental code derived from
A tool for making simple-style text posters or wallpapers with high resolution.
PurePoster PurePoster is a fancy tool for making arbitrary-resolution, simple-style posters or wallpapers with text in center. Functionality PurePoste
Fast batch image resizer and rotator for JPEG and PNG images.
imgp is a command line image resizer and rotator for JPEG and PNG images.
VSR-Transformer - This paper proposes a new Transformer for video super-resolution (called VSR-Transformer).
VSR-Transformer By Jiezhang Cao, Yawei Li, Kai Zhang, Luc Van Gool This paper proposes a new Transformer for video super-resolution (called VSR-Transf
EMNLP'2021: Simple Entity-centric Questions Challenge Dense Retrievers
EntityQuestions This repository contains the EntityQuestions dataset as well as code to evaluate retrieval results from the the paper Simple Entity-ce
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
GLaRA: Graph-based Labeling Rule Augmentation for Weakly Supervised Named Entity Recognition
This is the source code for: Context-aware Entity Typing in Knowledge Graphs.
This is the source code for: Context-aware Entity Typing in Knowledge Graphs.
EMNLP'2021: Simple Entity-centric Questions Challenge Dense Retrievers
EntityQuestions This repository contains the EntityQuestions dataset as well as code to evaluate retrieval results from the the paper Simple Entity-ce
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR
Source code for "Pack Together: Entity and Relation Extraction with Levitated Marker"
PL-Marker Source code for Pack Together: Entity and Relation Extraction with Levitated Marker. Quick links Overview Setup Install Dependencies Data Pr
A spaCy wrapper of OpenTapioca for named entity linking on Wikidata
spaCyOpenTapioca A spaCy wrapper of OpenTapioca for named entity linking on Wikidata. Table of contents Installation How to use Local OpenTapioca Vizu
[EMNLP 2021] MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations
MuVER This repo contains the code and pre-trained model for our EMNLP 2021 paper: MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity
Tool to add main subject to items on Wikidata using a WMFs CirrusSearch for named entity recognition or a manually supplied list of QIDs
ItemSubjector Tool made to add main subject statements to items based on the title using a home-brewed CirrusSearch-based Named Entity Recognition alg
“Data Augmentation for Cross-Domain Named Entity Recognition” (EMNLP 2021)
Data Augmentation for Cross-Domain Named Entity Recognition Authors: Shuguang Chen, Gustavo Aguilar, Leonardo Neves and Thamar Solorio This repository
【Arxiv】Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution
SANet Exploring Separable Attention for Multi-Contrast MR Image Super-Resolution Dependencies numpy==1.18.5 scikit_image==0.16.2 torchvision==0.8.1 to
Official implementation of Deep Burst Super-Resolution
Deep-Burst-SR Official implementation of Deep Burst Super-Resolution Publication: Deep Burst Super-Resolution. Goutam Bhat, Martin Danelljan, Luc Van
PyTorch Implementation of "Light Field Image Super-Resolution with Transformers"
LFT PyTorch implementation of "Light Field Image Super-Resolution with Transformers", arXiv 2021. [pdf]. Contributions: We make the first attempt to a
[EMNLP 2021] Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training
RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
Real-ESRGAN Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data Ported from https://github.com/xinntao/Real-ESRGAN Depend
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment
This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced in the paper titled "BanglaBERT: Combating Embedding Barrier in Multilingual Models for Low-Resource Language Understanding".
BanglaBERT This repository contains the official release of the model "BanglaBERT" and associated downstream finetuning code and datasets introduced i
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
This repository contains the code for EMNLP-2021 paper "Word-Level Coreference Resolution"
Word-Level Coreference Resolution This is a repository with the code to reproduce the experiments described in the paper of the same name, which was a
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
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
BasicVSR BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond Ported from https://github.com/xinntao/BasicSR Dependencie
Lite-HRNet: A Lightweight High-Resolution Network
LiteHRNet Benchmark 🔥 🔥 Based on MMsegmentation 🔥 🔥 Cityscapes FCN resize concat config mIoU last mAcc last eval last mIoU best mAcc best eval bes
Dataset and Code for ICCV 2021 paper "Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme"
Dataset and Code for RealVSR Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme Xi Yang, Wangmeng Xiang,
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
Cross Quality LFW: A database for Analyzing Cross-Resolution Image Face Recognition in Unconstrained Environments
Cross-Quality Labeled Faces in the Wild (XQLFW) Here, we release the database, evaluation protocol and code for the following paper: Cross Quality LFW
Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
Pytorch-NLU,一个中文文本分类、序列标注工具包,支持中文长文本、短文本的多类、多标签分类任务,支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech tagging and word segmentation.
Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices, ACM Multimedia 2021
Codes for ECBSR Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices Xindong Zhang, Hui Zeng, Lei Zhang ACM Multimedia 202
Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)
Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021) This repository is the official PyTorc
Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch
Image Super-Resolution via Iterative Refinement Paper | Project Brief This is a unoffical implementation about Image Super-Resolution via Iterative Re
Unofficial PyTorch Implementation of UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch
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
The official implementation of the Interspeech 2021 paper WSRGlow: A Glow-based Waveform Generative Model for Audio Super-Resolution.
WSRGlow The official implementation of the Interspeech 2021 paper WSRGlow: A Glow-based Waveform Generative Model for Audio Super-Resolution. Audio sa
Source Code For Template-Based Named Entity Recognition Using BART
Template-Based NER Source Code For Template-Based Named Entity Recognition Using BART Training Training train.py Inference inference.py Corpus ATIS (h
SwinIR: Image Restoration Using Swin Transformer
SwinIR: Image Restoration Using Swin Transformer This repository is the official PyTorch implementation of SwinIR: Image Restoration Using Shifted Win
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
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
pytorch implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802
PyTorch SRResNet Implementation of Paper: "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"(https://arxiv.org/abs
Deploy an inference API on AWS (EC2) using FastAPI Docker and Github Actions
Deploy an inference API on AWS (EC2) using FastAPI Docker and Github Actions To learn more about this project: medium blog post The goal of this proje
Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning
structshot Code and data for paper "Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning", Yi Yang and Arz
PyTorch version of the paper 'Enhanced Deep Residual Networks for Single Image Super-Resolution' (CVPRW 2017)
About PyTorch 1.2.0 Now the master branch supports PyTorch 1.2.0 by default. Due to the serious version problem (especially torch.utils.data.dataloade
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"
This is an official implementation of the High-Resolution Transformer for Dense Prediction.
High-Resolution Transformer for Dense Prediction Introduction This is the official implementation of High-Resolution Transformer (HRT). We present a H
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data arXiv This is the code base for weakly supervised NER. We provide a
DAN: Unfolding the Alternating Optimization for Blind Super Resolution
DAN-Basd-on-Openmmlab DAN: Unfolding the Alternating Optimization for Blind Super Resolution We reproduce DAN via mmediting based on open-sourced code
Practical Single-Image Super-Resolution Using Look-Up Table
Practical Single-Image Super-Resolution Using Look-Up Table [Paper] Dependency Python 3.6 PyTorch glob numpy pillow tqdm tensorboardx 1. Training deep
Collective Multi-type Entity Alignment Between Knowledge Graphs (WWW'20)
CG-MuAlign A reference implementation for "Collective Multi-type Entity Alignment Between Knowledge Graphs", published in WWW 2020. If you find our pa
[ACL-IJCNLP 2021] Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
CLNER The code is for our ACL-IJCNLP 2021 paper: Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning CLNER is a
Open-World Entity Segmentation
Open-World Entity Segmentation Project Website Lu Qi*, Jason Kuen*, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Zhe Lin, Philip Torr, Jiaya Jia This projec
Official PyTorch implementation of "VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization" (CVPR 2021)
VITON-HD — Official PyTorch Implementation VITON-HD: High-Resolution Virtual Try-On via Misalignment-Aware Normalization Seunghwan Choi*1, Sunghyun Pa
[ACM MM 2021] Joint Implicit Image Function for Guided Depth Super-Resolution
Joint Implicit Image Function for Guided Depth Super-Resolution This repository contains the code for: Joint Implicit Image Function for Guided Depth
"Inductive Entity Representations from Text via Link Prediction" @ The Web Conference 2021
Inductive entity representations from text via link prediction This repository contains the code used for the experiments in the paper "Inductive enti
Unofficial PyTorch Implementation of UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation This is an unofficial PyTorch
Collect super-resolution related papers, data, repositories
Collect super-resolution related papers, data, repositories
PyTorch implementation of 1712.06087 "Zero-Shot" Super-Resolution using Deep Internal Learning
Unofficial PyTorch implementation of "Zero-Shot" Super-Resolution using Deep Internal Learning Unofficial Implementation of 1712.06087 "Zero-Shot" Sup
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation
Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded
Pytorch implementation of Deep Recursive Residual Network for Super Resolution (DRRN)
DRRN-pytorch This is an unofficial implementation of "Deep Recursive Residual Network for Super Resolution (DRRN)", CVPR 2017 in Pytorch. [Paper] You
Open-World Entity Segmentation
Open-World Entity Segmentation Project Website Lu Qi*, Jason Kuen*, Yi Wang, Jiuxiang Gu, Hengshuang Zhao, Zhe Lin, Philip Torr, Jiaya Jia This projec
Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch
SRDenseNet-pytorch Implementation of paper: "Image Super-Resolution Using Dense Skip Connections" in PyTorch (http://openaccess.thecvf.com/content_ICC
Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.
Real-ESRGAN Colab Demo for Real-ESRGAN . Portable Windows executable file. You can find more information here. Real-ESRGAN aims at developing Practica
Code for Text Prior Guided Scene Text Image Super-Resolution
Code for Text Prior Guided Scene Text Image Super-Resolution
Implementation of CVPR 2020 Dual Super-Resolution Learning for Semantic Segmentation
Dual super-resolution learning for semantic segmentation 2021-01-02 Subpixel Update Happy new year! The 2020-12-29 update of SISR with subpixel conv p
A text augmentation tool for named entity recognition.
neraug This python library helps you with augmenting text data for named entity recognition. Augmentation Example Reference from An Analysis of Simple
Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
vid2vid Project | YouTube(short) | YouTube(full) | arXiv | Paper(full) Pytorch implementation for high-resolution (e.g., 2048x1024) photorealistic vid
Project page of the paper 'Analyzing Perception-Distortion Tradeoff using Enhanced Perceptual Super-resolution Network' (ECCVW 2018)
EPSR (Enhanced Perceptual Super-resolution Network) paper This repo provides the test code, pretrained models, and results on benchmark datasets of ou
PyTorch code for our ECCV 2020 paper "Single Image Super-Resolution via a Holistic Attention Network"
HAN PyTorch code for our ECCV 2020 paper "Single Image Super-Resolution via a Holistic Attention Network" This repository is for HAN introduced in the
A heterogeneous entity-augmented academic language model based on Open Academic Graph (OAG)
Library | Paper | Slack We released two versions of OAG-BERT in CogDL package. OAG-BERT is a heterogeneous entity-augmented academic language model wh
Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference
RawVSR This repo contains the official codes for our paper: Exploit Camera Raw Data for Video Super-Resolution via Hidden Markov Model Inference Xiaoh
Source code for "UniRE: A Unified Label Space for Entity Relation Extraction.", ACL2021.
UniRE Source code for "UniRE: A Unified Label Space for Entity Relation Extraction.", ACL2021. Requirements python: 3.7.6 pytorch: 1.8.1 transformers:
PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).
Image Super-Resolution with Non-Local Sparse Attention This repository is for NLSN introduced in the following paper "Image Super-Resolution with Non-
PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR)
This is a PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR), using subpixel convolution to optimize the inference speed of TecoGAN VSR model. Please refer to the official implementation ESPCN and TecoGAN for more information.
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data
Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re
NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling @ INTERSPEECH 2021 Accepted
NU-Wave — Official PyTorch Implementation NU-Wave: A Diffusion Probabilistic Model for Neural Audio Upsampling Junhyeok Lee, Seungu Han @ MINDsLab Inc
A PyTorch Reimplementation of TecoGAN: Temporally Coherent GAN for Video Super-Resolution
TecoGAN-PyTorch Introduction This is a PyTorch reimplementation of TecoGAN: Temporally Coherent GAN for Video Super-Resolution (VSR). Please refer to
PyTorch implementation of Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution, IJCNN 2021.
GCResNet PyTorch implementation of Graph Convolutional Networks in Feature Space for Image Deblurring and Super-resolution, IJCNN 2021. The code will
Implementation for our AAAI2021 paper (Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction).
SSAN Introduction This is the pytorch implementation of the SSAN model (see our AAAI2021 paper: Entity Structure Within and Throughout: Modeling Menti
Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition"
Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition", accepted at ACL 2021. For details of the model and experiments, please see our paper.
Learning To Have An Ear For Face Super-Resolution
Learning To Have An Ear For Face Super-Resolution [Project Page] This repository contains demo code of our CVPR2020 paper. Training and evaluation on
Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate in order to predict and suggest complex annotations. Markup also provides integrated access to existing and custom ontologies, enabling the prediction and suggestion of ontology mappings based on the text you're annotating.
Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate in order to predict and suggest complex annotations. Markup also provides integrated access to existing and custom ontologies, enabling the prediction and suggestion of ontology mappings based on the text you're annotating.
UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation
UnivNet UnivNet: A Neural Vocoder with Multi-Resolution Spectrogram Discriminators for High-Fidelity Waveform Generation. Training python train.py --c
Cross-Document Coreference Resolution
Cross-Document Coreference Resolution This repository contains code and models for end-to-end cross-document coreference resolution, as decribed in ou
CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation
CoCosNet v2: Full-Resolution Correspondence Learning for Image Translation (CVPR 2021, oral presentation) CoCosNet v2: Full-Resolution Correspondence
Evaluation Pipeline for our ECCV2020: Journey Towards Tiny Perceptual Super-Resolution.
Journey Towards Tiny Perceptual Super-Resolution Test code for our ECCV2020 paper: https://arxiv.org/abs/2007.04356 Our x4 upscaling pre-trained model
Just a script for detecting the lanes in any car game (not just gta 5) with specific resolution and road design ( very basic and limited )
GTA-5-Lane-detection Just a script for detecting the lanes in any car game (not just gta 5) with specific resolution and road design ( very basic and
Source code and dataset for ACL2021 paper: "ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning".
ERICA Source code and dataset for ACL2021 paper: "ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive L
Ecommerce product title recognition package
revizor This package solves task of splitting product title string into components, like type, brand, model and article (or SKU or product code or you
Code for C2-Matching (CVPR2021). Paper: Robust Reference-based Super-Resolution via C2-Matching.
C2-Matching (CVPR2021) This repository contains the implementation of the following paper: Robust Reference-based Super-Resolution via C2-Matching Yum
Chinese clinical named entity recognition using pre-trained BERT model
Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging This repository contains an implementation
Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)
MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J