Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"

Related tags

Deep LearningDSN-IQA
Overview

DSN-IQA

Source code for paper "Deep Superpixel-based Network for Blind Image Quality Assessment"

Requirements

  • Python >=3.8.0
  • Pytorch >=1.7.1

Usage with default setting

To train and test, directly use following code in 4 gpus situation:

CUDA_VISIBLE_DEVICES="0,1,2,3" python -m torch.distributed.launch --nproc_per_node 4 ddpWorker.py

Dataset

  • Most of them can be directly gained from Google.
  • For FLIVE, please visit here

Citation

To be continued...

Acknowledge

https://github.com/DensoITLab/ss-with-RIM

https://github.com/SSL92/hyperIQA

https://github.com/yichengsu/ICIP2020-WSP-IQA

Owner
No description~
Implementation of the final project of the course DDA6309 Probabilistic Graphical Model

Task-aware Joint CWS and POS (TCwsPos) This is the implementation of the final project of the course DDA6309 Probabilistic Graphical Models, The Chine

Peng 1 Dec 26, 2021
pq is a jq-like Pickle file viewer

pq PQ is a jq-like viewer/processing tool for pickle files. howto # pq '' file.pkl {'other': 456, 'test': 123} # pq 'table' file.pkl |other|test| | 45

3 Mar 15, 2022
PyTorch Code for the paper "VSE++: Improving Visual-Semantic Embeddings with Hard Negatives"

Improving Visual-Semantic Embeddings with Hard Negatives Code for the image-caption retrieval methods from VSE++: Improving Visual-Semantic Embeddings

Fartash Faghri 441 Dec 05, 2022
[Preprint] ConvMLP: Hierarchical Convolutional MLPs for Vision, 2021

Convolutional MLP ConvMLP: Hierarchical Convolutional MLPs for Vision Preprint link: ConvMLP: Hierarchical Convolutional MLPs for Vision By Jiachen Li

SHI Lab 143 Jan 03, 2023
SMD-Nets: Stereo Mixture Density Networks

SMD-Nets: Stereo Mixture Density Networks This repository contains a Pytorch implementation of "SMD-Nets: Stereo Mixture Density Networks" (CVPR 2021)

Fabio Tosi 115 Dec 26, 2022
E2VID_ROS - E2VID_ROS: E2VID to a real-time system

E2VID_ROS Introduce We extend E2VID to a real-time system. Because Python ROS ca

Robin Shaun 7 Apr 17, 2022
Lite-HRNet: A Lightweight High-Resolution Network

LiteHRNet Benchmark ๐Ÿ”ฅ ๐Ÿ”ฅ Based on MMsegmentation ๐Ÿ”ฅ ๐Ÿ”ฅ Cityscapes FCN resize concat config mIoU last mAcc last eval last mIoU best mAcc best eval bes

16 Dec 12, 2022
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption

โฑ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor

Lukas Hedegaard 21 Dec 22, 2022
Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR

Codebase for "INVASE: Instance-wise Variable Selection" Authors: Jinsung Yoon, James Jordon, Mihaela van der Schaar Paper: Jinsung Yoon, James Jordon,

Jinsung Yoon 50 Nov 11, 2022
Offcial implementation of "A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Prediction, ICCV-2021".

HF2-VAD Offcial implementation of "A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Predictio

76 Dec 21, 2022
IEGAN โ€” Official PyTorch Implementation Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation

IEGAN โ€” Official PyTorch Implementation Independent Encoder for Deep Hierarchical Unsupervised Image-to-Image Translation Independent Encoder for Deep

30 Nov 05, 2022
Official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right"

Surface Form Competition This is the official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right" We p

Peter West 46 Dec 23, 2022
Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"

On the Bottleneck of Graph Neural Networks and its Practical Implications This is the official implementation of the paper: On the Bottleneck of Graph

75 Dec 22, 2022
PyTorch implementation for paper Neural Marching Cubes.

NMC PyTorch implementation for paper Neural Marching Cubes, Zhiqin Chen, Hao Zhang. Paper | Supplementary Material (to be updated) Citation If you fin

Zhiqin Chen 109 Dec 27, 2022
Training Structured Neural Networks Through Manifold Identification and Variance Reduction

Training Structured Neural Networks Through Manifold Identification and Variance Reduction This repository is a pytorch implementation of the Regulari

0 Dec 23, 2021
Large-scale language modeling tutorials with PyTorch

Large-scale language modeling tutorials with PyTorch ์•ˆ๋…•ํ•˜์„ธ์š”. ์ €๋Š” TUNiB์—์„œ ๋จธ์‹ ๋Ÿฌ๋‹ ์—”์ง€๋‹ˆ์–ด๋กœ ๊ทผ๋ฌด ์ค‘์ธ ๊ณ ํ˜„์›…์ž…๋‹ˆ๋‹ค. ์ด ์ž๋ฃŒ๋Š” ๋Œ€๊ทœ๋ชจ ์–ธ์–ด๋ชจ๋ธ ๊ฐœ๋ฐœ์— ํ•„์š”ํ•œ ์—ฌ๋Ÿฌ๊ฐ€์ง€ ๊ธฐ์ˆ ๋“ค์„ ์†Œ๊ฐœ๋“œ๋ฆฌ๊ธฐ ์œ„ํ•ด ๋งˆ๋ จํ•˜์˜€์œผ๋ฉฐ ๊ธฐ๋ณธ์ ์œผ๋กœ

TUNiB 172 Dec 29, 2022
ใ€Arxivใ€‘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

36 Jan 05, 2023
StarGAN2 for practice

StarGAN2 for practice This version of StarGAN2 (coined as 'Post-modern Style Transfer') is intended mostly for fellow artists, who rarely look at scie

vadim epstein 87 Sep 24, 2022
Rendering color and depth images for ShapeNet models.

Color & Depth Renderer for ShapeNet This library includes the tools for rendering multi-view color and depth images of ShapeNet models. Physically bas

Yinyu Nie 41 Dec 19, 2022
Colar: Effective and Efficient Online Action Detection by Consulting Exemplars, CVPR 2022.

Colar: Effective and Efficient Online Action Detection by Consulting Exemplars This repository is the official implementation of Colar. In this work,

LeYang 246 Dec 13, 2022