Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks

Related tags

Deep Learning Lac-GwcNet
Overview

Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks

Contributions

  • A novel pairwise feature LSP to extract structural information, which is beneficial for accurate matching especially when the illumination of the image pair is imbalanced
  • A novel disparity refinement method CSR (or DSR to save memory) to deal with outliers that are difficult to match, e.g. disparity discontinuities and occluded regions.

Dependencies：

Training on SceneFlow

python train.py --data_path (your Scene Flow data folder)

Finetuning on KITTI

python KITTI_ft.py --data_path (your KITTI training data folder) --load_path (the path of the model trained on SceneFlow)
Comments
  • Testing/evaluation phase

    Testing/evaluation phase

    Good evening, I just managed to finish the training on SceneFlow and finetuning step by using the training images of KITTI_2015 and i was wondering how to evaluate the model againist the testing images. Could you give me any tips? Should i run the test_kitti.py? If so, do i need to provide the checkpoint.tar generated in the finetuning step?

    opened by Salvatore-tech 4
  • Dataloading error

    Dataloading error

    Hi, i'm trying to train the network on KITTI2015 dataset available at the following link https://s3.eu-central-1.amazonaws.com/avg-kitti/data_scene_flow.zip but i'm getting an error while loading the images.

    I'm attaching the log below, can you clarify if the dataset structure should be changed? Thanks in advance

    File "train.py", line 40, in all_limg, all_rimg, all_ldisp, test_limg, test_rimg, test_ldisp = sf.sf_loader(args.data_path) File "/home/s.starace/Lac-GwcNet-main/dataloader/sceneflow_loader.py", line 32, in sf_loader monkaa_img = filepath + [x for x in image if 'monkaa' in x][0] IndexError: list index out of range

    opened by Salvatore-tech 4
  • Tensor pushing from GPU to CPU

    Tensor pushing from GPU to CPU

    Good evening, I'm bit struggling with the storing place of tensors, in fact when running python KITTI_ft.py --data_path /home/s.starace/Dataset/KITTI_2015/training \ --load_path ./preTrained/SceneFlow.pth
    It suppose that tensors should be pushed first on the CPU before converting them through numpy... could you confirm that? Thanks in advance tensorErrorLog.txt

    opened by Salvatore-tech 3
  • test on Oxford RobotCar

    test on Oxford RobotCar

    Hi, I have tested on the stereo images of Oxford RobotCar with pretrained model kitti2015.pth directly. However, the output disparity images have some white or black patches with extremely unsmooth grayscale values, and some parts of the building have insignificant differences in disparity values. Have you done any tests on the robotcar dataset? Is there any parameter adjustment that can optimize the above problem?

    opened by XC-Young 2
  • some detail question

    some detail question

    can i have your anothor contact details. I have send your email message, if convenient, please give me a reply! Thanks very much for your good work and reply in a busy time~

    opened by luyao-cv 4
  • kitti_15 results reproduction D1 is not align with the open weights

    kitti_15 results reproduction D1 is not align with the open weights

    thanks for your good work, but i have downloaded the sceneflow weights, and trained the kitti_15 datasets using the kitti_ft.py as the command "python KITTI_ft.py --data_path /data/kitti_2015/training/ --gpu_id 4 --load_path SceneFlow.pth --no_cuda --batch_size 4" , however, the results is not good as the open weights. can you provide the command to get the results as good as the open weight? Thanks very much!

    opened by luyao-cv 1
  • About test code？

    About test code？

    Hello, thank you very much for your code, I would like to ask why you need to input the , gt_tensor to predict the display when testing?

    with torch.no_grad():
    pred_disp = model(limg_tensor, rimg_tensor, gt_tensor)
    opened by BreezeJing 1
Owner
null
GitHub
RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching

RAFT-Stereo: Multilevel Recurrent Field Transforms for Stereo Matching This repository contains the source code for our paper: RAFT-Stereo: Multilevel

Princeton Vision & Learning Lab 328 Jan 9, 2023
Siamese-nn-semantic-text-similarity - A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task

Siamese Deep Neural Networks for Semantic Text Similarity PyTorch A repository c

Shahrukh Khan 32 Dec 15, 2022
Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch .

PyTorch-High-Res-Stereo-Depth-Estimation Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch. Stereo dep

Ibai Gorordo 26 Nov 24, 2022
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

null 912 Jan 8, 2023
Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-local Spatial-Temporal Similarity

This repository is the official PyTorch implementation of Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and Non-local Spatial-Temporal Similarity

hippopmonkey 4 Dec 11, 2022
Sharpened cosine similarity torch - A Sharpened Cosine Similarity layer for PyTorch

Sharpened Cosine Similarity A layer implementation for PyTorch Install At your c

Brandon Rohrer 203 Nov 30, 2022
Lightweight stereo matching network based on MobileNetV1 and MobileNetV2

MobileStereoNet: Towards Lightweight Deep Networks for Stereo Matching

Cognitive Systems Research Group 139 Nov 30, 2022
the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet]

BGNet This repository contains the code for our CVPR 2021 paper Bilateral Grid Learning for Stereo Matching Network [BGNet] Environment Python 3.6.* C

3DCV developer 87 Nov 29, 2022
Stacked Recurrent Hourglass Network for Stereo Matching

SRH-Net: Stacked Recurrent Hourglass Introduction This repository is supplementary material of our RA-L submission, which helps reviewers to understan

null 28 Jan 3, 2023
Pytorch reimplementation of PSM-Net: "Pyramid Stereo Matching Network"

This is a Pytorch Lightning version PSMNet which is based on JiaRenChang/PSMNet. use python main.py to start training. PSM-Net Pytorch reimplementatio

XIAOTIAN LIU 1 Nov 25, 2021
The official implementation code of "PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense Reconstruction."

PlantStereo This is the official implementation code for the paper "PlantStereo: A Stereo Matching Benchmark for Plant Surface Dense Reconstruction".

Wang Qingyu 14 Nov 28, 2022
✨✨✨An awesome open source toolbox for stereo matching.

OpenStereo This is an awesome open source toolbox for stereo matching. Supported Methods: BM SGM(T-PAMI'07) GCNet(ICCV'17) PSMNet(CVPR'18) StereoNet(E

Wang Qingyu 6 Nov 4, 2022
The code of “Similarity Reasoning and Filtration for Image-Text Matching” [AAAI2021]

SGRAF PyTorch implementation for AAAI2021 paper of “Similarity Reasoning and Filtration for Image-Text Matching”. It is built on top of the SCAN and C

Ronnie_IIAU 149 Dec 22, 2022
Code for the paper "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021)

MASTER-PyTorch PyTorch reimplementation of "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021). This projec

Wenwen Yu 255 Dec 29, 2022
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod

Jason Kuen 17 Jul 4, 2022
[CVPR 21] Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting, IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2021.

Vectorization and Rasterization: Self-Supervised Learning for Sketch and Handwriting, CVPR 2021. Ayan Kumar Bhunia, Pinaki nath Chowdhury, Yongxin Yan

Ayan Kumar Bhunia 44 Dec 12, 2022
Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Context Terms

LESA Introduction This repository contains the official implementation of Locally Enhanced Self-Attention: Rethinking Self-Attention as Local and Cont

Chenglin Yang 20 Dec 31, 2021
Pytorch codes for "Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation"

Self-Supervised-MVS This repository is the official PyTorch implementation of our AAAI 2021 paper: "Self-supervised Multi-view Stereo via Effective Co

hongbin_xu 127 Jan 4, 2023
Code for C2-Matching (CVPR2021). Paper: Robust Reference-based Super-Resolution via C2-Matching.

C2-Matching (CVPR2021) This repository contains the implementation of the following paper: Robust Reference-based Super-Resolution via C2-Matching Yum

Yuming Jiang 151 Dec 26, 2022