douwenhao68 Goto Github PK

-

[ICCV 2021 Oral] Deep Evidential Action Recognition

a-general-3d-object-detection-codebse.

A general 3D object detection codebse.

aleatoric-epistemic-uncertainty

Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"

apollo

An open autonomous driving platform

awesome-attention-mechanism-in-cv

:punch: CV中常用注意力模块;即插即用模块;ViT模型. PyTorch Implementation Collection of Attention Module and Plug&Play Module

bevfusion

BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

cbam.pytorch

Non-official implement of Paper：CBAM: Convolutional Block Attention Module

concretedropout

Code for Concrete Dropout as presented in https://arxiv.org/abs/1705.07832

cross-modality-knowledge-distillation

Cross-Modality Knowledge Distillation Network for Monocular 3D Object Detection (ECCV 2022 Oral)

dair-v2x

dcm-net

This work is based on our paper "DualConvMesh-Net: Joint Geodesic and Euclidean Convolutions on 3D Meshes", which appeared at the IEEE Conference On Computer Vision And Pattern Recognition (CVPR) 2020.

deep-evidential-regression

Learn fast, scalable, and calibrated measures of uncertainty using neural networks!

dl-uncertainty

"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).

dmc

dropoutuncertaintyexps

Experiments used in "Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning"

evaluating-scalable-bayesian-deep-learning-methods-for-robust-computer-vision

Official implementation of "Evaluating Scalable Bayesian Deep Learning Methods for Robust Computer Vision", CVPR Workshops 2020.

evidential-deep-learning-to-quantify-classification-uncertainty

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

external-attention-pytorch

🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

gaussian_yolov3

Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving (ICCV, 2019)

graphrcnn

Graph R-CNN: Towards Accurate 3D Object Detection with Semantic-Decorated Local Graph (ECCV 2022, Oral) :fire:

howtolivelonger

程序员延寿指南 | A programmer's guide to live longer

lidar-bonnetal

Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving

my-implementation-of-what-uncertainties-do-we-need-in-bayesian-deep-learning-for-computer-vision

Pytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple version)

open3d-semantic-kitti-vis

Open3D based Semantic KITTI LiDAR dataset visualization tool

opencda_dataset

A generalized framework for prototyping full-stack cooperative driving automation applications under CARLA+SUMO.

pmf

Perception-aware multi-sensor fusion for 3D LiDAR semantic segmentation (ICCV 2021)

point-transformer-pytorch

Implementation of the Point Transformer layer, in Pytorch

priornetworks

progressive_meshes

Implementation of progressive meshes by Hugues Hoppe

pysumo

Python module for running SUMO traffic simulations