[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects

Overview

[NeurIPS 2021] Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects

YouTube | arXiv

                 

Prerequisites

Kaolin is available here: https://github.com/NVIDIAGameWorks/kaolin

Running

Examples

The code can be easily run by:

python optimize.py

Running with your inputs:

python optimize.py --im examples/vol_im.png --bgr examples/vol_bgr.png
python optimize.py --im examples/aerobie_im.png --bgr examples/aerobie_bgr.png
python optimize.py --im examples/pen_im.png --bgr examples/pen_bgr.png

The results will be written to the output folder.

Reference

Examples If you use this repository, please cite the following publication:

@misc{sfb,
  title = {Shape from Blur: Recovering Textured 3D Shape and Motion of Fast Moving Objects},
  author = {Denys Rozumnyi and Martin R. Oswald and Vittorio Ferrari and Marc Pollefeys},
  booktitle = {NeurIPS},
  month = {Dec},
  year = {2021}
}
You might also like...
Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022)
Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022)

Pop-Out Motion Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian (CVPR 2022) Jihyun Lee*, Minhyuk Sung*, Hyunjin Kim, Tae-Ky

Code for Discriminative Sounding Objects Localization (NeurIPS 2020)
Code for Discriminative Sounding Objects Localization (NeurIPS 2020)

Discriminative Sounding Objects Localization Code for our NeurIPS 2020 paper Discriminative Sounding Objects Localization via Self-supervised Audiovis

A hand tracking demo made with mediapipe where you can control lights with pinching your fingers and moving your hand up/down.

HandTrackingBrightnessControl A hand tracking demo made with mediapipe where you can control lights with pinching your fingers and moving your hand up

Deep Implicit Moving Least-Squares Functions for 3D Reconstruction
Deep Implicit Moving Least-Squares Functions for 3D Reconstruction

DeepMLS: Deep Implicit Moving Least-Squares Functions for 3D Reconstruction This repository contains the implementation of the paper: Deep Implicit Mo

MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera
MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

MonoRec: Semi-Supervised Dense Reconstruction in Dynamic Environments from a Single Moving Camera

Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data

LiDAR-MOS: Moving Object Segmentation in 3D LiDAR Data This repo contains the code for our paper: Moving Object Segmentation in 3D LiDAR Data: A Learn

Simulation of moving particles under microscopic imaging

Simulation of moving particles under microscopic imaging Install scipy numpy scikit-image tiffile Run python simulation.py Read result https://imagej

High-performance moving least squares material point method (MLS-MPM) solver.
High-performance moving least squares material point method (MLS-MPM) solver.

High-Performance MLS-MPM Solver with Cutting and Coupling (CPIC) (MIT License) A Moving Least Squares Material Point Method with Displacement Disconti

Predict multi paths to a moving person depending on his trajectory history.
Predict multi paths to a moving person depending on his trajectory history.

Multi-future Trajectory Prediction The project is about using the Multiverse model to make possible multible-future trajectory prediction for a seen p

Comments
  • cannot import name 'total_variation' from 'kornia'

    cannot import name 'total_variation' from 'kornia'

    hi!

    what an interesting work!

    I have some trouble running the test demo. I have downloaded the newest kornia from pip and tried this https://github.com/kornia/kornia/discussions/1290, but still, get the problem. I wonder if you could give your environment requirements to run the test.

    thx :)

    Traceback (most recent call last):
      File "optimize.py", line 7, in <module>
        from shapefromblur import *
      File "/dev-data/xxx/projects/SfB/ShapeFromBlur-main/shapefromblur.py", line 12, in <module>
        from models.loss import *
      File "/dev-data/xxx/projects/SfB/ShapeFromBlur-main/models/loss.py", line 3, in <module>
        from kornia import total_variation
    ImportError: cannot import name 'total_variation' from 'kornia'
    
    opened by Ayxm1412 2
Releases(v1.0)
Owner
Denys Rozumnyi
PhD student at ETH Zurich.
Denys Rozumnyi
Voice Conversion by CycleGAN (语音克隆/语音转换):CycleGAN-VC3

CycleGAN-VC3-PyTorch 中文说明 | English This code is a PyTorch implementation for paper: CycleGAN-VC3: Examining and Improving CycleGAN-VCs for Mel-spectr

Kun Ma 110 Dec 24, 2022
ETMO: Evolutionary Transfer Multiobjective Optimization

ETMO: Evolutionary Transfer Multiobjective Optimization To promote the research on ETMO, benchmark problems are of great importance to ETMO algorithm

Songbai Liu 0 Mar 16, 2021
A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning", CIKM-21

ANEMONE A PyTorch implementation of "ANEMONE: Graph Anomaly Detection with Multi-Scale Contrastive Learning", CIKM-21 Dependencies python==3.6.1 dgl==

Graph Analysis & Deep Learning Laboratory, GRAND 30 Dec 14, 2022
YOLO5Face: Why Reinventing a Face Detector (https://arxiv.org/abs/2105.12931)

Introduction Yolov5-face is a real-time,high accuracy face detection. Performance Single Scale Inference on VGA resolution(max side is equal to 640 an

DeepCam Shenzhen 1.4k Jan 07, 2023
[WACV 2020] Reducing Footskate in Human Motion Reconstruction with Ground Contact Constraints

Reducing Footskate in Human Motion Reconstruction with Ground Contact Constraints Official implementation for Reducing Footskate in Human Motion Recon

Virginia Tech Vision and Learning Lab 38 Nov 01, 2022
Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets This is the official PyTorch implementation for the paper Rapid Neural A

48 Dec 26, 2022
Post-Training Quantization for Vision transformers.

PTQ4ViT Post-Training Quantization Framework for Vision Transformers. We use the twin uniform quantization method to reduce the quantization error on

Zhihang Yuan 61 Dec 28, 2022
Angle data is a simple data type.

angledat Angle data is a simple data type. Installing + using Put angledat.py in the main dir of your project. Import it and use. Comments Comments st

1 Jan 05, 2022
Testing and Estimation of structural breaks in Stata

xtbreak estimating and testing for many known and unknown structural breaks in time series and panel data. For an overview of xtbreak test see xtbreak

Jan Ditzen 13 Jun 19, 2022
Towards uncontrained hand-object reconstruction from RGB videos

Towards uncontrained hand-object reconstruction from RGB videos Yana Hasson, Gül Varol, Ivan Laptev and Cordelia Schmid Project page Paper Table of Co

Yana 69 Dec 27, 2022
[ICCV'21] Neural Radiance Flow for 4D View Synthesis and Video Processing

NeRFlow [ICCV'21] Neural Radiance Flow for 4D View Synthesis and Video Processing Datasets The pouring dataset used for experiments can be download he

44 Dec 20, 2022
Build fully-functioning computer vision models with PyTorch

Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. Inferenc

Alan Bi 576 Dec 29, 2022
Discriminative Condition-Aware PLDA

DCA-PLDA This repository implements the Discriminative Condition-Aware Backend described in the paper: L. Ferrer, M. McLaren, and N. Brümmer, "A Speak

Luciana Ferrer 31 Aug 05, 2022
Deep GPs built on top of TensorFlow/Keras and GPflow

GPflux Documentation | Tutorials | API reference | Slack What does GPflux do? GPflux is a toolbox dedicated to Deep Gaussian processes (DGP), the hier

Secondmind Labs 107 Nov 02, 2022
Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Set Recognition"

Adversarial Reciprocal Points Learning for Open Set Recognition Official PyTorch implementation of "Adversarial Reciprocal Points Learning for Open Se

Guangyao Chen 78 Dec 28, 2022
An alarm clock coded in Python 3 with Tkinter

Tkinter-Alarm-Clock An alarm clock coded in Python 3 with Tkinter. Run python3 Tkinter Alarm Clock.py in a terminal if you have Python 3. NOTE: This p

CodeMaster7000 1 Dec 25, 2021
Official pytorch implementation of the AAAI 2021 paper Semantic Grouping Network for Video Captioning

Semantic Grouping Network for Video Captioning Hobin Ryu, Sunghun Kang, Haeyong Kang, and Chang D. Yoo. AAAI 2021. [arxiv] Environment Ubuntu 16.04 CU

Hobin Ryu 43 Nov 25, 2022
NeuralForecast is a Python library for time series forecasting with deep learning models

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate m

Nixtla 1.1k Jan 03, 2023
A project which aims to protect your privacy using inexpensive hardware and easily modifiable software

Protecting your privacy using an ESP32, an IR sensor and a python script This project, which I personally call the "never-gonna-catch-me-in-the-act-ev

8 Oct 10, 2022
MIRACLE (Missing data Imputation Refinement And Causal LEarning)

MIRACLE (Missing data Imputation Refinement And Causal LEarning) Code Author: Trent Kyono This repository contains the code used for the "MIRACLE: Cau

van_der_Schaar \LAB 15 Dec 29, 2022