From 0bef4a1cce7445d9fc5157e2e22055fc313c05b7 Mon Sep 17 00:00:00 2001 From: Christiano Gava Date: Sun, 5 Nov 2023 14:20:30 +0100 Subject: [PATCH] First draft Signed-off-by: Christiano Gava --- .gitattributes | 2 + index.html | 679 +++++++++++++++++- resources/bank_00000160.jpg | 3 + resources/barbershop_00000020.jpg | 3 + resources/berlinStreet_00000083.jpg | 3 + resources/berlin_00000140.jpg | 3 + resources/classroom_00000210.jpg | 3 + resources/corridorAV_00000088.jpg | 3 + resources/galileo_00000000.jpg | 3 + resources/garage_00001080.jpg | 3 + resources/harmony_00000250.jpg | 3 + resources/harmony_anchor_00000000.jpg | 3 + resources/harmony_satellite_00000001.jpg | 3 + resources/harmony_satellite_00000002.jpg | 3 + resources/harmony_satellite_00000003.jpg | 3 + resources/harmony_satellite_00000004.jpg | 3 + resources/harmony_satellite_00000005.jpg | 3 + resources/harmony_satellite_00000006.jpg | 3 + resources/harmony_satellite_00000007.jpg | 3 + resources/harmony_satellite_00000008.jpg | 3 + resources/harmony_satellite_00000009.jpg | 3 + resources/hauptbahnhof_00000069.jpg | 3 + resources/italianFlat_00000040.jpg | 3 + resources/kartu_00000180.jpg | 3 + resources/loneMonk_00000560.jpg | 3 + resources/medievalPort_00000000.jpg | 3 + resources/middleEast_00002030.jpg | 3 + resources/otterbergChurch_00000015.jpg | 3 + resources/pascal_00000000.jpg | 3 + resources/passion_00000240.jpg | 3 + resources/rainbow_00000440.jpg | 3 + resources/seoul_00000080.jpg | 3 + resources/shapespark_00000200.jpg | 3 + resources/showroom_00001170.jpg | 3 + resources/simple_00000260.jpg | 3 + resources/stMartinsplatz_00000022.jpg | 3 + resources/stadiumKL_00000036.jpg | 3 + resources/tokyo_00000040.jpg | 3 + resources/uni_00000022.jpg | 3 + resources/urbanCanyon_00002370.jpg | 3 + resources/vitoria_00000070.jpg | 3 + resources/vitoria_170_198.jpg | 3 + resources/vitoria_depth_170_198.jpg | 3 + ...uperpoint_gt_matches_00000170_00000198.jpg | 3 + resources/vitoria_topview_mesh.png | 3 + resources/warehouse_00000340.jpg | 3 + 46 files changed, 812 insertions(+), 1 deletion(-) create mode 100644 .gitattributes create mode 100644 resources/bank_00000160.jpg create mode 100644 resources/barbershop_00000020.jpg create mode 100644 resources/berlinStreet_00000083.jpg create mode 100644 resources/berlin_00000140.jpg create mode 100644 resources/classroom_00000210.jpg create mode 100644 resources/corridorAV_00000088.jpg create mode 100644 resources/galileo_00000000.jpg create mode 100644 resources/garage_00001080.jpg create mode 100644 resources/harmony_00000250.jpg create mode 100644 resources/harmony_anchor_00000000.jpg create mode 100644 resources/harmony_satellite_00000001.jpg create mode 100644 resources/harmony_satellite_00000002.jpg create mode 100644 resources/harmony_satellite_00000003.jpg create mode 100644 resources/harmony_satellite_00000004.jpg create mode 100644 resources/harmony_satellite_00000005.jpg create mode 100644 resources/harmony_satellite_00000006.jpg create mode 100644 resources/harmony_satellite_00000007.jpg create mode 100644 resources/harmony_satellite_00000008.jpg create mode 100644 resources/harmony_satellite_00000009.jpg create mode 100644 resources/hauptbahnhof_00000069.jpg create mode 100644 resources/italianFlat_00000040.jpg create mode 100644 resources/kartu_00000180.jpg create mode 100644 resources/loneMonk_00000560.jpg create mode 100644 resources/medievalPort_00000000.jpg create mode 100644 resources/middleEast_00002030.jpg create mode 100644 resources/otterbergChurch_00000015.jpg create mode 100644 resources/pascal_00000000.jpg create mode 100644 resources/passion_00000240.jpg create mode 100644 resources/rainbow_00000440.jpg create mode 100644 resources/seoul_00000080.jpg create mode 100644 resources/shapespark_00000200.jpg create mode 100644 resources/showroom_00001170.jpg create mode 100644 resources/simple_00000260.jpg create mode 100644 resources/stMartinsplatz_00000022.jpg create mode 100644 resources/stadiumKL_00000036.jpg create mode 100644 resources/tokyo_00000040.jpg create mode 100644 resources/uni_00000022.jpg create mode 100644 resources/urbanCanyon_00002370.jpg create mode 100644 resources/vitoria_00000070.jpg create mode 100644 resources/vitoria_170_198.jpg create mode 100644 resources/vitoria_depth_170_198.jpg create mode 100644 resources/vitoria_superpoint_gt_matches_00000170_00000198.jpg create mode 100644 resources/vitoria_topview_mesh.png create mode 100644 resources/warehouse_00000340.jpg diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..3a24117 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,2 @@ +*.jpg filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text diff --git a/index.html b/index.html index 557db03..cdb2b79 100644 --- a/index.html +++ b/index.html @@ -1 +1,678 @@ -Hello World + + + + + + + + SphereCraft + + + + + +
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+ SphereCraft: A Dataset for Spherical Keypoint Detection,
Matching and Camera Pose Estimation
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+ Christiano Gava1 +
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+ Yunmin Cho2 +
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+ Federico Raue1 +
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+ Sebastian Palacio1 +
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+ Alain Pagani1 +
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+ Andreas Dengel1,3 +
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1 DFKI 2 Aimmo Germany GmbH 3 University of Kaiserslautern-Landau
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+ Blender projects + 3D meshes + + Spherical images + + Depth maps + + Ground truth keypoint correspondences +
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Accepted at WACV-2024
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Abstract

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+ This paper introduces SphereCraft, a dataset specifically designed for spherical keypoint detection, matching, and camera pose estimation. + The dataset addresses the limitations of existing datasets by providing extracted keypoints from various detectors, along with their ground-truth correspondences. + Synthetic scenes with photo-realistic rendering and accurate 3D meshes are included, as well as real-world scenes acquired from different spherical cameras. + SphereCraft enables the development and evaluation of algorithms targeting multiple camera viewpoints, advancing the state-of-the-art in computer vision tasks involving spherical images. +
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Overview

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+ Our dataset comprises 21 synthetic scenes of different types, sizes, and complexity and yields over 2M image pairs for training and testing spherical keypoint matching models. + We generate indoor and outdoor synthetic scenes with high-resolution RGB spherical images along with their depth maps and ground truth camera poses. + A selection of popular handcrafted and learned keypoints is then extracted from each image and accurate ground truth keypoint correspondences are established. + A highly accurate 3D mesh from each synthetic scene is also included. + The resulting data (RGB images, depth maps, camera poses, 3D meshes, keypoints and their correspondences) allows future approaches to be trained and evaluated on exactly the same data. + Additionally, we release all Blender projects so other researchers can optionally render the same scenes at different resolutions or create their own version of the data according to their needs. +

+ For each synthetic scene, we manually place a set of cameras to homogeneously cover it. + We refer to this initial set as anchor cameras. + For each anchor camera, we randomly generate a set of satellite cameras in its vicinity. + Akin to data augmentation, the idea is to automatically produce several novel views of the scene from many different positions and orientations. + For instance, the figure below shows an anchor image (top left) along with its 9 satellite images. +
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+ The resolution of the rendered spherical images and depth maps is 2048x1024 pixels. + Below is a sample from each synthetic scene. + The number in parenthesis indicates the number of images in that scene. +
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+ Bank (930) + + Barbershop (80) + + Berlin (280) +
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+ Classroom (370) + + Garage (1090) + + Harmony (380) +
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+ Italian Flat (270) + + Kartu (640) + + Lone Monk (670) +
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+ Medieval Port (2160) + + Middle East (4300) + + Passion (600) +
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+ Rainbow (930) + + Seoul (330) + + Shapespark (860) +
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+ Showroom (1340) + + Simple (310) + + Tokyo (90) +
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+ Urban Canyon (4090) + + Vitoria (550) + + Warehouse (900) +
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+ Real-World Scenes +
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+ Along with synthetic scenes, we provide another 9 real scenes, captured with Civetta and Ricoh Theta-S cameras. + They convey 4 indoor and 5 outdoor scenes of different sizes and complexity, with resolutions considerably higher than the synthetic images. + Images captured with Civetta are 7070x3535 pixels, whereas those acquired with Theta-S are 5376x2688 pixels. + Unlike synthetic scenes, here ground truth depth maps, camera poses and keypoint correspondences are not available, but we provide keypoints extracted at the resolutions aforementioned. + Once again, the number in parenthesis indicates the number of images in that scene. +
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+ Berlin Street (186) + + Church (54) + + Corridors (116) +
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+ Meeting Room 1 (18) + + Meeting Room 2 (21) + + Stadium (74) +
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+ Town Square (35) + + Train Station (112) + + Uni (71) +
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Download SphereCraft

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+ Donwload link will be available soon. +
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Code

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+ Link to SphereCraft's github page will be available soon. +
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+ The template for this website is borrowed from Richard Zhang. +
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