Vu Tuan Anh's repositories
architectural_style_transfer
Code and data release for ICCP 2022 paper "Time-of-Day Neural Style Transfer for Architectural Photographs".
Semantic-Segmentation-Architectures-Implemented-in-PyTorch
https://meetshah1995.github.io/semantic-segmentation/deep-learning/pytorch/visdom/2017/06/01/semantic-segmentation-over-the-years.html
tuananh1007.github.io
My personal page
MarineInst20M
The official dataset repository of "MarineInst: A Foundation Model for Marine Image Analysis with Instance Visual Description". ECCV 2024.
stylecity3d
[ECCV 2024] StyleCity: Large-Scale 3D Urban Scenes Stylization with Vision-and-Text Reference via Progressive Optimization
3d-vision-transformers
A list of 3D computer vision papers with Transformers
Awesome-Instance-Segmentation
Some papers about instance segmentation
Awesome-Transformer-Attention
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
bibtex-tidy
Cleaner and Formatter for BibTeX files
diffusion_models
All about the fundamentals and working of Diffusion Models
EffectivePyTorch
PyTorch tutorials and best practices.
LargeScaleNeRFPytorch
1. Weekly classified NeRF literature. 2. Non-official implementation of Block-NeRF and Mega-NeRF in Pytorch. 3. Train your large-scale NeRF in the wild.
latexify_py
A library to generate LaTeX expression from Python code.
Mesh_Segmentation
some materials about mesh segmentation, including papers, videos, codes, and so on. Updating every day!
Networks-Beyond-Attention
A compilation of network architectures for vision and others without usage of self-attention mechanism
ODISE
Official PyTorch implementation of ODISE: Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models [CVPR 2023 Highlight]
point-cloud-utils
A Python library for common tasks on 3D point clouds
scalable-pytorch-sinkhorn
Fast, Memory-Efficient Approximate Wasserstein Distances. This repository contains PyTorch code to compute fast p-Wasserstein distances between d-dimensional point clouds using the Sinkhorn Algorithm. This implementation uses linear memory overhead and is stable in float32, runs on the GPU, and fully differentiable.