codename1995

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

tuning_playbook

A playbook for systematically maximizing the performance of deep learning models.

paper-reading

深度学习经典、新论文逐段精读

SummaryOfLoanSuspension

全国各省市停贷通知汇总

numpy-100

100 numpy exercises (with solutions)

dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

learning_research

本人的科研经验

Awesome-Transformer-Attention

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

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

bolei_awesome_posters

CVPR and NeurIPS poster examples and templates. May we have in-person poster session soon!

Awesome-LLM-3D

Awesome-LLM-3D: a curated list of Multi-modal Large Language Model in 3D world Resources

KPConv-PyTorch

Kernel Point Convolution implemented in PyTorch

Awesome-Masked-Autoencoders

A collection of literature after or concurrent with Masked Autoencoder (MAE) (Kaiming He el al.).

spvnas

[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

Codes-for-PVKD

Point-to-Voxel Knowledge Distillation for LiDAR Semantic Segmentation (CVPR 2022)

OpenPCSeg

OpenPCSeg: Open Source Point Cloud Segmentation Toolbox and Benchmark

Occupancy-MAE

Official implementation of our TIV'23 paper: Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders

Forge_VFM4AD

A comprehensive survey of forging vision foundation models for autonomous driving, including challenges, methodologies, and opportunities.

ALSO

ALSO: Automotive Lidar Self-supervision by Occupancy estimation

BoxeR

Code release for "BoxeR: Box-Attention for 2D and 3D Transformers"

RandLA-Net-pytorch

:four_leaf_clover: Pytorch Implementation of RandLA-Net (https://arxiv.org/abs/1911.11236)

GD-MAE

GD-MAE: Generative Decoder for MAE Pre-training on LiDAR Point Clouds (CVPR 2023)

TARL

[CVPR'23] TARL: Temporal Consistent 3D LiDAR Representation Learning for Semantic Perception in Autonomous Driving

SensatUrban-BEV-Seg3D

An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc.

GeoMAE

This is the official implementation of the paper - GeoMAE: Masked Geometric Target Prediction for Self-supervised Point Cloud Pre-Training

kprnet

Urban3D-2021-2nd

The 2nd solution (68.1 mIoU) for 1st Urban3D challenge.

Timetuning

Time Does Tell: Self-Supervised Time-Tuning of Dense Image Representations ICCV23

ml-notebooks

Deep Learning Tutorials and Notebooks

public-resources

This repository offers several public resources that I curated.