Official implementation for the paper "Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection"

Related tags

Deep LearningAttentivePrototypeSFUDA
Overview

Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection

PyTorch code release of the paper "Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection",

by Deepti Hegde, Vishal M. Patel

[arXiv]

image

(Currently has instructions for model inference and evaluation only, training steps to be updated soon.)

Follow the instructions for installation and implementation of the method for each base object detection network in the respective folders SECOND-iou and PointRCNN

Dataset preperation

  1. Download the relevant datasets: KITTI , Waymo , nuScenes

  2. Organize each folder inside data like the following

AttentivePrototypeSFUDA

├── data (main data folder)
│   ├── kitti
│   │   │── ImageSets
│   │   │── training
│   │   │   ├──calib & velodyne & label_2 & image_2 & (optional: planes)
│   │   │── testing
│   │   │   ├──calib & velodyne & image_2
|
|
│   ├── nuscenes
│   │   │── v1.0-trainval (or v1.0-mini if you use mini)
│   │   │   │── samples
│   │   │   │── sweeps
│   │   │   │── maps
│   │   │   │── v1.0-trainval  
|
|
│   ├── waymo
│   │   │── ImageSets
│   │   │── raw_data
│   │   │   │── segment-xxxxxxxx.tfrecord
|   |   |   |── ...
|   |   |── waymo_processed_data
│   │   │   │── segment-xxxxxxxx/
|   |   |   |── ...
│   │   │── pcdet_gt_database_train_sampled_xx/
│   │   │── pcdet_waymo_dbinfos_train_sampled_xx.pkl  
|
|
├── PointRCNN
|   ├── data (link to main data folder)
|   ├── pointrcnn_attention
├── SECOND-iou
|   ├── data (link to main data folder)
|   ├── pcdet
|   ├── tools

We implement the proposed method for two object detectors, SECOND-iou and PointRCNN for several domain shift scenarios. You can find the folder of pretrained models here. Find specific model downloads and their corresponding config files below.

| SECOND-iou |

Domain shift Model file Configuration file
Waymo -> KITTI download link
Waymo -> nuScenes download link
nuScenes -> KITTI download link

| PointRCNN |

Domain shift Model file Configuration file
Waymo -> KITTI download link
KITTI -> nuScenes download link
nuScenes -> KITTI download link

Follow the instructions to implement the method in the folders SECOND-iou and PointRCNN

Owner
Deepti Hegde
PhD student at Johns Hopkins University, Vision and Image Understanding Lab.
Deepti Hegde
GitHub Repository
MODNet: Trimap-Free Portrait Matting in Real Time

MODNet is a model for real-time portrait matting with only RGB image input.

Zhanghan Ke 2.8k Dec 30, 2022
atmaCup #11 の Public 4th / Pricvate 5th Solution のリポジトリです。

#11 atmaCup 2021-07-09 ~ 2020-07-21 に行われた #11 [初心者歓迎! / 画像編] atmaCup のリポジトリです。結果は Public 4th / Private 5th でした。 フレームワークは PyTorch で、実装は pytorch-image-m

Tawara 12 Apr 07, 2022
Learning kernels to maximize the power of MMD tests

Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga

Danica J. Sutherland 201 Dec 17, 2022
"Exploring Vision Transformers for Fine-grained Classification" at CVPRW FGVC8

FGVC8 Exploring Vision Transformers for Fine-grained Classification paper presented at the CVPR 2021, The Eight Workshop on Fine-Grained Visual Catego

Marcos V. Conde 19 Dec 06, 2022
Official PyTorch code for Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021)

Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution (MANet, ICCV2021) This repository is the official PyTorc

Jingyun Liang 139 Dec 29, 2022
ML-Decoder: Scalable and Versatile Classification Head

ML-Decoder: Scalable and Versatile Classification Head Paper Official PyTorch Implementation Tal Ridnik, Gilad Sharir, Avi Ben-Cohen, Emanuel Ben-Baru

189 Jan 04, 2023
Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis (CVPR2022)

Multi-View Consistent Generative Adversarial Networks for 3D-aware Image Synthesis Multi-View Consistent Generative Adversarial Networks for 3D-aware

Xuanmeng Zhang 78 Dec 10, 2022
DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

dm_control: DeepMind Infrastructure for Physics-Based Simulation. DeepMind's software stack for physics-based simulation and Reinforcement Learning en

DeepMind 3k Dec 31, 2022
Contains code for Deep Kernelized Dense Geometric Matching

DKM - Deep Kernelized Dense Geometric Matching Contains code for Deep Kernelized Dense Geometric Matching We provide pretrained models and code for ev

Johan Edstedt 83 Dec 23, 2022
The Deep Learning with Julia book, using Flux.jl.

Deep Learning with Julia DL with Julia is a book about how to do various deep learning tasks using the Julia programming language and specifically the

Logan Kilpatrick 67 Dec 25, 2022
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference

PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based

Jacob Gildenblat 836 Dec 26, 2022
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation

EFENet EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation Code is a bit messy now. I woud clean up soon. For training the EF

Yaping Zhao 19 Nov 05, 2022
Plugin for Gaffer providing direct acess to asset from PolyHaven.com. Only HDRIs at the moment, Cycles and Arnold supported

GafferHaven Plugin for Gaffer providing direct acess to asset from PolyHaven.com. Only HDRIs are supported at the moment, in Cycles and Arnold lights.

Jakub Vondra 6 Jan 26, 2022
(CVPR 2021) Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds

BRNet Introduction This is a release of the code of our paper Back-tracing Representative Points for Voting-based 3D Object Detection in Point Clouds,

86 Oct 05, 2022
[ACL-IJCNLP 2021] "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets"

EarlyBERT This is the official implementation for the paper in ACL-IJCNLP 2021 "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets" by

VITA 13 May 11, 2022
DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021)

DPT This repo is the official implementation of DPT: Deformable Patch-based Transformer for Visual Recognition (ACM MM2021). We provide code and model

CASIA-IVA-Lab 111 Dec 21, 2022
This is an official implementation of the CVPR2022 paper "Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots".

Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots Blind2Unblind Citing Blind2Unblind @inproceedings{wang2022blind2unblind, tit

demonsjin 58 Dec 06, 2022
Learning multiple gaits of quadruped robot using hierarchical reinforcement learning

Learning multiple gaits of quadruped robot using hierarchical reinforcement learning We propose a method to learn multiple gaits of quadruped robot us

Yunho Kim 17 Dec 11, 2022
In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits

Fastapi + MLflow + streamlit Setup env. I hope I covered all. pip install -r requirements.txt Start app Go in the root dir and run these Streamlit str

76 Nov 23, 2022
Reimplement of SimSwap training code

SimSwap-train Reimplement of SimSwap training code Instructions 1.Environment Preparation （1）Refer to the README document of SIMSWAP to configure the

seeprettyface.com 111 Dec 31, 2022