Computer Vision is an elective course of MSAI, SCSE, NTU, Singapore

Overview

[AI6121] Computer Vision

====== I M P O R T A N T ======

The content in this repository should exclusively be utilized in sharing solutions for projects, communicating ideas for related problems, and references to similar assignments. If you are a student facing an assignment with the same or similar topics, you can use this repository as a reference, while the final report should include the citations of the repository. If you submit an assignment without proper acknowledgment after referring to this repository, you may be considered PLAGIARISM by your instructor, and the author will not pay ANY responsibility for this. Please refer to your teacher's and your school's instructions for the determination of academic integrity.

Moreover, if you are taking the AI6121 course, do not be stupid. You can utilize the materials here as a reference to construct your own assignment and reflect the citation to this repository in the final report. If you copy the code without citing it, you have violated NTU's academic integrity and are involved in plagiarism.

Please refer to the following links for NTU's determination of academic integrity and plagiarism:

https://ts.ntu.edu.sg/sites/intranet/dept/tlpd/ai/Pages/NTU-Academic-Integrity-Policy.aspx

https://ts.ntu.edu.sg/sites/intranet/dept/tlpd/ai/Pages/default.aspx

https://ts.ntu.edu.sg/sites/policyportal/new/Documents/All%20including%20NIE%20staff%20and%20students/Student%20Academic%20Integrity%20Policy.pdf

If you think the professor is easy to fool, think again.
You know who you are.

====== D I S C L A I M E R ======

This repository should only be used for reasonable academic discussions. I, the owner of this repository, never and will never ALLOWING another student to copy this assignment as their own. In such circumstances, I do not violate NTU's statement on academic integrity as of the time this repository is open (15/01/2022). I am not responsible for any future plagiarism using the content of this repository.



====== I N T R O D U C T I O N ======

[AI6121] Computer Vision is an elective course of Master of Science in Artificial Intelligence Graduate Programme (MSAI), School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore. The repository corresponds to the AI6121 of Semester 1, AY2021-2022, starting from 08/2021. The instructor of this course is Prof. Lu Shijian.

The projects of this course consist of two individual Assignments, one individual Literature Review, and one group Project. The topic and score of the assignment are shown below. Since multiple people complete the group work, I do not have the right to disclose the report, others' codes, and grades individually so that the relevant parts will be hidden, and the group project only presents part of the code and report finished by myself.

In addition, the generated output image is not given in the file in order to save space since all the source code has been provided. Data are uploaded after all output folders are emptied.

Type Topic Grade
Assignment 1 Histogram Equalization 20.0 / 20.0
Assignment 2 Disparity Map 18.5 / 20.0
Literature Review Self-supervised Image Denoise 20.0 / 20.0
Group Project Neural Network N.A. / 40.0

====== A C K N O W L E D G E M E N T ======

All of above projects are designed by Prof. Lu Shijian.

Owner
HT. Li
HT. Li
Official implementation of our paper "LLA: Loss-aware Label Assignment for Dense Pedestrian Detection" in Pytorch.

LLA: Loss-aware Label Assignment for Dense Pedestrian Detection This project provides an implementation for "LLA: Loss-aware Label Assignment for Dens

35 Dec 06, 2022
Reimplementation of Dynamic Multi-scale filters for Semantic Segmentation.

Paddle implementation of Dynamic Multi-scale filters for Semantic Segmentation.

Hongqiang.Wang 2 Nov 01, 2021
Ontologysim: a Owlready2 library for applied production simulation

Ontologysim: a Owlready2 library for applied production simulation Ontologysim is an open-source deep production simulation framework, with an emphasi

10 Nov 30, 2022
Implementation of ConvMixer in TensorFlow and Keras

ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in that it operates directly on

Sayan Nath 8 Oct 03, 2022
Code for sound field predictions in domains with impedance boundaries. Used for generating results from the paper

Code for sound field predictions in domains with impedance boundaries. Used for generating results from the paper

DTU Acoustic Technology Group 11 Dec 17, 2022
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

LiangWei Jiang 2.5k Jan 02, 2023
EM-POSE 3D Human Pose Estimation from Sparse Electromagnetic Trackers.

EM-POSE: 3D Human Pose Estimation from Sparse Electromagnetic Trackers This repository contains the code to our paper published at ICCV 2021. For ques

Facebook Research 62 Dec 14, 2022
yolov5 deepsort 行人 车辆 跟踪 检测 计数

yolov5 deepsort 行人 车辆 跟踪 检测 计数 实现了 出/入 分别计数。 默认是 南/北 方向检测,若要检测不同位置和方向,可在 main.py 文件第13行和21行,修改2个polygon的点。 默认检测类别:行人、自行车、小汽车、摩托车、公交车、卡车。 检测类别可在 detect

554 Dec 30, 2022
Basics of 2D and 3D Human Pose Estimation.

Human Pose Estimation 101 If you want a slightly more rigorous tutorial and understand the basics of Human Pose Estimation and how the field has evolv

Sudharshan Chandra Babu 293 Dec 14, 2022
Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning"

CMSF Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning" Requirements Python = 3.7.6 PyTorch

4 Nov 25, 2022
A Python implementation of the Locality Preserving Matching (LPM) method for pruning outliers in image matching.

LPM_Python A Python implementation of the Locality Preserving Matching (LPM) method for pruning outliers in image matching. The code is established ac

AoxiangFan 11 Nov 07, 2022
CTF challenges from redpwnCTF 2021

redpwnCTF 2021 Challenges This repository contains challenges from redpwnCTF 2021 in the rCDS format; challenge information is in the challenge.yaml f

redpwn 27 Dec 07, 2022
Implementation of "Bidirectional Projection Network for Cross Dimension Scene Understanding" CVPR 2021 (Oral)

Bidirectional Projection Network for Cross Dimension Scene Understanding CVPR 2021 (Oral) [ Project Webpage ] [ arXiv ] [ Video ] Existing segmentatio

Hu Wenbo 135 Dec 26, 2022
An Inverse Kinematics library aiming performance and modularity

IKPy Demo Live demos of what IKPy can do (click on the image below to see the video): Also, a presentation of IKPy: Presentation. Features With IKPy,

Pierre Manceron 481 Jan 02, 2023
A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)

A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)

Vikash Sehwag 65 Dec 19, 2022
Code used to generate the results appearing in "Train longer, generalize better: closing the generalization gap in large batch training of neural networks"

Train longer, generalize better - Big batch training This is a code repository used to generate the results appearing in "Train longer, generalize bet

Elad Hoffer 145 Sep 16, 2022
Rethinking the U-Net architecture for multimodal biomedical image segmentation

MultiResUNet Rethinking the U-Net architecture for multimodal biomedical image segmentation This repository contains the original implementation of "M

Nabil Ibtehaz 308 Jan 05, 2023
Tutorials, assignments, and competitions for MIT Deep Learning related courses.

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

Lex Fridman 9.5k Jan 07, 2023
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data

Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for

Facebook Research 6.8k Jan 01, 2023
Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

Auto-ViML Automatically Build Variant Interpretable ML models fast! Auto_ViML is pronounced "auto vimal" (autovimal logo created by Sanket Ghanmare) N

AutoViz and Auto_ViML 397 Dec 30, 2022