by-liu

academic-kickstart

📝 Easily create a beautiful website using Academic, Hugo, and Netlify

albumentations-demo

The service for the demonstration of transforms in Albumentations library

by-liu.github.io

calibration-framework

Python Framework to calibrate confidence estimates of classifiers like Neural Networks

CALS

Code for our method CALS (Class Adaptive Label Smoothing) for network calibration. To Appear at CVPR 2023. Paper: https://arxiv.org/abs/2211.15088

ConfKD

Code for our paper : Mixed-supervised segmentation: Confidence maximization helps knowledge distillation. https://arxiv.org/abs/2109.10902

donut

Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022

lightning-hydra-template

Deep Learning project template best practices with Pytorch Lightning, Hydra, Tensorboard.

MbLS

Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/2111.15430

SegLossBias

Code for the paper : Do we really need dice? The hidden region-size biases of segmentation losses. MeDIA 2023. https://www.sciencedirect.com/science/article/abs/pii/S136184152300275X

by-liu/MbLS

Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/2111.15430

by-liu/SegLossBias

Code for the paper : Do we really need dice? The hidden region-size biases of segmentation losses. MeDIA 2023. https://www.sciencedirect.com/science/article/abs/pii/S136184152300275X

by-liu/CALS

Code for our method CALS (Class Adaptive Label Smoothing) for network calibration. To Appear at CVPR 2023. Paper: https://arxiv.org/abs/2211.15088

by-liu/ConfKD

Code for our paper : Mixed-supervised segmentation: Confidence maximization helps knowledge distillation. https://arxiv.org/abs/2109.10902

by-liu/academic-kickstart

📝 Easily create a beautiful website using Academic, Hugo, and Netlify

by-liu/albumentations-demo

The service for the demonstration of transforms in Albumentations library

by-liu/by-liu.github.io

by-liu/calibration-framework

Python Framework to calibrate confidence estimates of classifiers like Neural Networks

by-liu/donut

Official Implementation of OCR-free Document Understanding Transformer (Donut) and Synthetic Document Generator (SynthDoG), ECCV 2022

by-liu/lightning-hydra-template

Deep Learning project template best practices with Pytorch Lightning, Hydra, Tensorboard.

by-liu/maskrcnn-benchmark

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

by-liu/MI-based-Regularized-Semi-supervised-Segmentation

This is a place holder for an incomming paper.

by-liu/mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

by-liu/moco

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

by-liu/MSL-student-becomes-master

by-liu/myutil

some personal scripts and config

by-liu/nnUNet

by-liu/OpenUnReID

Open-source toolbox for unsupervised or domain adaptive object re-ID.

by-liu/personal_website

by-liu/Pytorch-UNet

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

by-liu/RetinalApp

by-liu/SegLoss

A collection of loss functions for medical image segmentation

by-liu/segmentation_viewer

A really simple tool to visualize different segmentation results

by-liu/SlowFast

PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.

by-liu/Swin-Transformer

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

by-liu/TA3N

[ICCV 2019 (Oral)] Temporal Attentive Alignment for Large-Scale Video Domain Adaptation (PyTorch)

by-liu/ttda