rubics-xuan Goto Github PK

agln

cm-masksd

This repo holds the official codes for CM-MaskSD, accepted by IEEE-TMM 2024.

explain_metric_learning

Code for paper: "Visual Explanation for Deep Metric Learning"

fremim

This repo holds the official code for the paper "FreMIM: Fourier Transform Meets Masked Image Modeling for Medical Image Segmentation".

gpts

leaked prompts of GPTs

haiway

Haiway Edge Computing OS

hrnet-semantic-segmentation

The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919

hsi-traditional-to-deep-models

Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.

ivg

This repo holds the official code and data for "Beyond Literal Descriptions: Understanding and Locating Open-World Objects Aligned with Human Intentions", which is accepted by ACL 2024 (Findings).

med-danet

Med-DANet Series (ECCV 2022 & WACV 2024)

mres

This repo holds the official code and data for "Unveiling Parts Beyond Objects: Towards Finer-Granularity Referring Expression Segmentation", accepted by CVPR 2024.

open_brats2020

Top 10 brats 2020 Solution

open_clip

An open source implementation of CLIP.

opt_questioner

Official PyTorch implementation of the paper "Enhancing Vision-Language Pre-Training with Jointly Learned Questioner and Dense Captioner"

repvgg

RepVGG: Making VGG-style ConvNets Great Again

rubics-xuan

GitHub Readme Stats

rubics-xuan.github.io

All project pages for our papers.

transbts

This repo provides the official code for : 1) TransBTS: Multimodal Brain Tumor Segmentation Using Transformer (https://arxiv.org/abs/2103.04430) , accepted by MICCAI2021. 2) TransBTSV2: Towards Better and More Efficient Volumetric Segmentation of Medical Images(https://arxiv.org/abs/2201.12785).

uni3d

[ICLR'24 Spotlight] Uni3D: 3D Visual Representation from BAAI

x-anylabeling

Effortless data labeling with AI support from Segment Anything and other awesome models.