Xu Luo's starred repositories
stanford_alpaca
Code and documentation to train Stanford's Alpaca models, and generate the data.
bolei_awesome_posters
CVPR and NeurIPS poster examples and templates. May we have in-person poster session soon!
flamingo-pytorch
Implementation of š¦© Flamingo, state-of-the-art few-shot visual question answering attention net out of Deepmind, in Pytorch
StreamYOLO
Real-time Object Detection for Streaming Perception, CVPR 2022
ORBIT-Dataset
The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.
inat_comp_2018
CNN training code for iNaturalist 2018 image classification competition
Bongard-HOI
[CVPR 2022 (oral)] Bongard-HOI for benchmarking few-shot visual reasoning
pytorch-meta-dataset
A non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification
Channel_Importance_FSL
[ICML 2022] Channel Importance Matters in Few-shot Image Classification
multimodal-meta-learn
Official code repository for "Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning" (published at ICLR 2023).
CloserLookAgainFewShot
[ICML 2023] A Closer Look at Few-shot Classification Again
UNICORN-MAML
PyTorch implementation of "How to Train Your MAML to Excel in Few-Shot Classification"
byol-convert
Code and model definition for converting the official BYOL weights to PyTorch
LabelHalluc
[AAAI 2022] Label Hallucination for Few-Shot Classification
contextual-squeeze-and-excitation
Official Pytorch implementation of the paper "Contextual Squeeze-and-Excitation for Efficient Few-Shot Image Classification" (NeurIPS 2022)
firth_bias_reduction
This repository contains the experiments conducted in the ICLR 2022 spotlight paper "On the Importance of Firth Bias Reduction in Few-Shot Classification".
highest_cited_ml_conference_paper
A github page that displays the highest cited machine learning conference paper.