Xu Ma

pointMLP-pytorch. [ICLR 2022 poster] Official PyTorch implementation of "Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework"

Context-Cluster. [ICLR 2023 Oral] Image as Set of Points

Rewrite-the-Stars. [CVPR 2024] Rewrite the Stars

Open-Set-Recognition. Open Set Recognition

DCANet. [arXiv 2020] Deep Connected Attention Networks

CollaborativeFiltering. matlab, collaborative filtering, MovieLens dataset，The movie recommendation system

FCViT. A Close Look at Spatial Modeling: From Attention to Convolution

LIVE. [CVPR 2022 Oral] Towards Layer-wise Image Vectorization

EfficientMod. [ICLR 2024 poster] Efficient Modulation for Vision Networks

DataMining. Java implementation of the classic Data mining (big data) algorithm. Create a new Java project, and copy this project to the SRC directory is ok.

SPANet. Codes of "SPANet: Spatial Pyramid Attention Network for Enhanced Image Recognition"

ORL3. Face recognition implement based on LDA, PCA and SVM.

Efficient_ImageNet_Classification. An efficient implementation for ImageNet classification

TSNE. Python

SPANet_TMM. Python

CenterLoss. A Discriminative Feature Learning Approach for Deep Face Recognition

DNN. A DNN learning project

Non-Local. Compare Non-Local, GC, SE and Global_Average_Pooling

L21FS. L21FS

Attention. Python

Dynamic-Conv. Python

NANet. Code for "Attention Meets Normalization and Beyond"

ResidualAttention. Python

SparseSENet. For REU project

ParameterFree. Official code for “Cascaded Context Dependency: An Extremely Lightweight Module for Deep Convolutional Neural Networks”

pointsMLP. Python

openmax. Python

DistKernel. Python

hpc_yolo3. an object detection framework for UNT REU 2019 project.

2PTWSVM. 2PTWSVM

token-shuffle. [Project Page] Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models

PRM. IJCAI 2020

ImageNet.fastai. Python

incrementalAD. This is a project for Incremental Anomaly Detection, which is written in MATLAB. The used techniques including: incremental LDA, incremental SVM, SMOTE, hard negative mining.

MLproject. The project for Machine Learning

RDANet. residual decoupled attention on imagenet

RDA_cifar_GCP. RDA on CIFAR100

detection. Python

imagenet_nv. Python

cifar. Python

Learning_keras. A learning demo for DNN based on keras

awesome-vision-transformers-comparison. A detailed comparsion of Recent Vision Transformers on ImageNet1k

imagenet.pytorch. Python

Library. all

mmdet1. Python

ECommerce. test

SuperPixelNet.

mmdetection3d-0.10.0. Python

RENYI.

OLTR. Python

DeepMetric. Python

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