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Welcome to My GitHub Profile!

My research interests lie at the intersection of Computer Vision and Deep Learning, with a specific focus on:

  • Self-Supervised Learning (SSL)
  • Generative AI
  • Remote Sensing
  • Low-Level Vision

🌐 Homepage: www.wgcban.com

Featured Projects

Self-Supervised Representation Learning

  • Guarding Barlow Twins Against Overfitting with Mixed Samples GitHub 🚨
  • AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders @ CVPR'23 GitHub

Generative AI

  • Unite and Conquer: Cross Dataset Multimodal Synthesis using Diffusion Models @ CVPR'23 GitHub

Remote Sensing

Change Detection

  • ChangeFormer: A Transformer-Based Siamese Network for Change Detection @ IGARSS'22 GitHub
  • DDPM-CD: Remote Sensing Change Detection using Denoising Diffusion Probabilistic Models GitHub
  • Revisiting Consistency Regularization for Semi-supervised Change Detection in Remote Sensing Images GitHub
  • Metric-CD: Deep Metric Learning for Unsupervised Remote Sensing Change Detection GitHub

Image Super-Resolution / Pansharpening

  • HyperTransformer: A Textural and Spectral Feature Fusion Transformer for Pansharpening @ CVPR'22 GitHub
  • DIP-HyperKite: Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction @ TGRS'22 GitHub

Segmentation

  • SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving @ ICRA'22 GitHub

SAR Despeckling

  • SAR-Transformer: Transformer-based SAR Image Despeckling @ IGARSS'22 GitHub
  • SAR-Overcomplete: SAR Despeckling Using Overcomplete Convolutional Networks @ IGARSS'22 GitHub
  • SAR-DDPM: SAR Despeckling using a Denoising Diffusion Probabilistic Model @ Geoscience and Remote Sensing Letters GitHub

Low-level Vision

  • Diffuse-Denoise-Count: Accurate Crowd-Counting with Diffusion Models GitHub

Chaminda Bandara's Projects

adamae icon adamae

[CVPR'23] AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning with Masked Autoencoders

adapters icon adapters

LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

apt icon apt

PyTorch Implementation of Attention Prompt Tuning: Parameter-Efficient Adaptation of Pre-Trained Models for Action Recognition

cd-sota-methods icon cd-sota-methods

Remote sensing change detection: state of the art methods and datasets

cdlab icon cdlab

Yet another repository for developing and benchmarking deep learning-based change detection methods.

change-detection-review icon change-detection-review

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

changeformer icon changeformer

[IGARSS'22]: A Transformer-Based Siamese Network for Change Detection

ddpm-cd icon ddpm-cd

Remote Sensing Change Detection using Denoising Diffusion Probabilistic Models

deep-image-translation-cd icon deep-image-translation-cd

This repository contains the software developed for the project of Heterogeneous Change Detection in Remote Sensing Images.

dip-hyperkite icon dip-hyperkite

[IEEE TGRS] DIP-HyperKite: Hyperspectral Pansharpening Based on Improved Deep Image Prior and Residual Reconstruction

dtcdscn icon dtcdscn

the implementation of the paper"Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model "

eccv2020_cucanet icon eccv2020_cucanet

Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution, ECCV, 2020. (PyTorch)

hypertransformer icon hypertransformer

[CVPR'22] HyperTransformer: A Textural and Spectral Feature Fusion Transformer for Pansharpening

kinetics icon kinetics

This repository is intended to host tools and demos for ActivityNet

lightly icon lightly

A python library for self-supervised learning on images.

llama icon llama

Inference code for LLaMA models

loveda icon loveda

[NeurIPS2021 Poster] LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation

mae icon mae

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

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