Official Implementation of SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations

Related tags

Deep LearningSimIPU
Overview

Official Implementation of SimIPU

  • SimIPU: Simple 2D Image and 3D Point Cloud Unsupervised Pre-Training for Spatial-Aware Visual Representations
  • Since the code is still waiting for release, if you have any question with reproduction, feel free to contact us. We will try our best to help you.
  • Currently, the core code of SimIPU is implemented in the commercial project. We are trying our best to make the code publicly available.
Comments
  • Question about augmentation

    Question about augmentation

    Hi, I'm a little confused about the data augmentation.

    1. How did you set img_aug when img_moco=True? It seems that we need an 'img_pipeline' in 'simipu_kitti.py', right?
    2. For 3D augmentation, it seems that it is done in this line. So the 3D augmentation is done based on the point features instead the raw points, right? If I want to try moco=True, how to set 3D augmentation? should I do this in the dataset building part? https://github.com/zhyever/SimIPU/blob/5b346e392c161a5e9fdde09b1692656bc7cd3faf/project_cl/decorator/inter_intro_decorator_moco_better.py#L394

    Looking forward to your reply. Many thanks.

    opened by sunnyHelen 2
  • error for env setup:ImportError: cannot import name 'ball_query_ext' from 'mmdet3d.ops.ball_query'

    error for env setup:ImportError: cannot import name 'ball_query_ext' from 'mmdet3d.ops.ball_query'

    Thanks for your insightful paper and clear code repo!

    Hi, I met with the ImportError: cannot import name 'ball_query_ext' from 'mmdet3d.ops.ball_query' when run the command bash tools/dist_train.sh project_cl/configs/simipu/simipu_kitti.py 1 --work_dir ./

    Do you know how to solve it?

    Traceback (most recent call last): File "tools/train.py", line 16, in from mmdet3d.apis import train_model File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/apis/init.py", line 1, in from .inference import (convert_SyncBN, inference_detector, File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/apis/inference.py", line 10, in from mmdet3d.core import (Box3DMode, DepthInstance3DBoxes, File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/core/init.py", line 2, in from .bbox import * # noqa: F401, F403 File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/core/bbox/init.py", line 4, in from .iou_calculators import (AxisAlignedBboxOverlaps3D, BboxOverlaps3D, File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/core/bbox/iou_calculators/init.py", line 1, in from .iou3d_calculator import (AxisAlignedBboxOverlaps3D, BboxOverlaps3D, File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/core/bbox/iou_calculators/iou3d_calculator.py", line 5, in from ..structures import get_box_type File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/core/bbox/structures/init.py", line 1, in from .base_box3d import BaseInstance3DBoxes File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/core/bbox/structures/base_box3d.py", line 5, in from mmdet3d.ops.iou3d import iou3d_cuda File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/ops/init.py", line 5, in from .ball_query import ball_query File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/ops/ball_query/init.py", line 1, in from .ball_query import ball_query File "/mnt/lustre/xxh/SimIPU-main/mmdet3d/ops/ball_query/ball_query.py", line 4, in from . import ball_query_ext ImportError: cannot import name 'ball_query_ext' from 'mmdet3d.ops.ball_query' (/mnt/lustre/xxh/SimIPU-main/mmdet3d/ops/ball_query/init.py)

    I noticed that you once met with the same error. https://github.com/open-mmlab/mmdetection3d/issues/503#issuecomment-847618114

    So, I would like to ask for your help~ Hopefully you have a good solution. :)

    opened by JerryX1110 2
  • A question about eq5 and eq6

    A question about eq5 and eq6

    Thanks for your inspiring work. I have some wonder about eq5 and eq6. As far as I know, After eq5, f should be a tensor which is a global feature with shape (batchsize * 2048 * 1 * 1), how can you sample corresponding image features by projection location? After all, there's no spatial information in f anymore. Or maybe you got features from a previous layer of ResNet? Looking forward to your reply.

    opened by lianchengmingjue 2
  • A question about Tab.5 in Ablation Study

    A question about Tab.5 in Ablation Study

    Thanks for your excellent work first! I have a question about Tab.5 in Ablation Study. Why "Scratch" equals "SimIPU w/o inter-module ", which means that the intra-module is useless?

    opened by Trent-tangtao 1
  • Have you tried not to crop gradient of f^{\alpha} in eq7?

    Have you tried not to crop gradient of f^{\alpha} in eq7?

    Hi, I like your good work! I am wondering have you tried not to crop the gradient of $f^{\alpha}$ in eq7? If you crop the gradient, it seems like the pertaining of the point branch cannot learn anything from the image branch.

    opened by Hiusam 1
  • issues about create_data

    issues about create_data

    Hi, thanks for sharing your great work. I encounter some issues during creating data by running create_data.py First create reduced point cloud for training set [ ] 0/3712, elapsed: 0s, ETA:Traceback (most recent call last): File "tools/create_data.py", line 247, in
    out_dir=args.out_dir)
    File "tools/create_data.py", line 24, in kitti_data_prep
    kitti.create_reduced_point_cloud(root_path, info_prefix)
    File "/mnt/lustre/chenzhuo1/hzha/SimIPU/tools/data_converter/kitti_converter.py", line 374, in create_reduced_point_cloud
    _create_reduced_point_cloud(data_path, train_info_path, save_path)
    File "/mnt/lustre/chenzhuo1/hzha/SimIPU/tools/data_converter/kitti_converter.py", line 314, in _create_reduced_point_cloud
    count=-1).reshape([-1, num_features])
    ValueError: cannot reshape array of size 461536 into shape (6)

    It seems to set the num_features=4 and front_camera_id=2? in this line: https://github.com/zhyever/SimIPU/blob/5b346e392c161a5e9fdde09b1692656bc7cd3faf/tools/data_converter/kitti_converter.py#L291

    I assume doing this can solve the problem but encounter another problem when Create GT Database of KittiDataset
    [ ] 0/3712, elapsed: 0s, ETA:Traceback (most recent call last):
    File "tools/create_data.py", line 247, in
    out_dir=args.out_dir)
    File "tools/create_data.py", line 44, in kitti_data_prep
    with_bbox=True) # for moca
    File "/mnt/lustre/chenzhuo1/hzha/SimIPU/tools/data_converter/create_gt_database.py", line 275, in create_groundtruth_database
    P0 = np.array(example['P0']).reshape(4, 4)
    KeyError: 'P0'

    Can you help me figure out how to solve these issues?

    opened by sunnyHelen 21
Owner
Zhyever
Keep going.
Zhyever
Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021.

EfficientZero (NeurIPS 2021) Open-source codebase for EfficientZero, from "Mastering Atari Games with Limited Data" at NeurIPS 2021. Thank you for you

Weirui Ye 671 Jan 03, 2023
3 Apr 20, 2022
Project NII pytorch scripts

project-NII-pytorch-scripts By Xin Wang, National Institute of Informatics, since 2021 I am a new pytorch user. If you have any suggestions or questio

Yamagishi and Echizen Laboratories, National Institute of Informatics 184 Dec 23, 2022
This is the first released system towards complex meters` detection and recognition, which is implemented by computer vision techniques.

A three-stage detection and recognition pipeline of complex meters in wild This is the first released system towards detection and recognition of comp

Yan Shu 19 Nov 28, 2022
Deep Reinforcement Learning for Keras.

Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml

Keras-RL 0 Dec 15, 2022
PyTorch code for our paper "Attention in Attention Network for Image Super-Resolution"

Under construction... Attention in Attention Network for Image Super-Resolution (A2N) This repository is an PyTorch implementation of the paper "Atten

Haoyu Chen 71 Dec 30, 2022
Centroid-UNet is deep neural network model to detect centroids from satellite images.

Centroid UNet - Locating Object Centroids in Aerial/Serial Images Introduction Centroid-UNet is deep neural network model to detect centroids from Aer

GIC-AIT 19 Dec 08, 2022
Implementation of association rules mining algorithms (Apriori|FPGrowth) using python.

Association Rules Mining Using Python Implementation of association rules mining algorithms (Apriori|FPGrowth) using python. As a part of hw1 code in

Pre 2 Nov 10, 2021
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

RuiLiu 65 Dec 20, 2022
null

DeformingThings4D dataset Video | Paper DeformingThings4D is an synthetic dataset containing 1,972 animation sequences spanning 31 categories of human

208 Jan 03, 2023
Exemplo de implementação do padrão circuit breaker em python

fast-circuit-breaker Circuit breakers existem para permitir que uma parte do seu sistema falhe sem destruir todo seu ecossistema de serviços. Michael

James G Silva 17 Nov 10, 2022
This program will stylize your photos with fast neural style transfer.

Neural Style Transfer (NST) Using TensorFlow Demo TensorFlow TensorFlow is an end-to-end open source platform for machine learning. It has a comprehen

Ismail Boularbah 1 Aug 08, 2022
Builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques

This project builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques.

20 Dec 30, 2022
a pytorch implementation of auto-punctuation learned character by character

Learning Auto-Punctuation by Reading Engadget Articles Link to Other of my work 🌟 Deep Learning Notes: A collection of my notes going from basic mult

Ge Yang 137 Nov 09, 2022
QR2Pass-project - A proof of concept for an alternative (passwordless) authentication system to a web server

QR2Pass This is a proof of concept for an alternative (passwordless) authenticat

4 Dec 09, 2022
This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods

pyLiDAR-SLAM This codebase proposes modular light python and pytorch implementations of several LiDAR Odometry methods, which can easily be evaluated

Kitware, Inc. 208 Dec 16, 2022
MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens

MSG-Transformer Official implementation of the paper MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens, by Jiemin

Hust Visual Learning Team 68 Nov 16, 2022
Point-NeRF: Point-based Neural Radiance Fields

Point-NeRF: Point-based Neural Radiance Fields Project Sites | Paper | Primary c

Qiangeng Xu 662 Jan 01, 2023
Self-supervised Deep LiDAR Odometry for Robotic Applications

DeLORA: Self-supervised Deep LiDAR Odometry for Robotic Applications Overview Paper: link Video: link ICRA Presentation: link This is the correspondin

Robotic Systems Lab - Legged Robotics at ETH Zürich 181 Dec 29, 2022
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".

Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re

Zhuang AI Group 30 Dec 19, 2022