Add GaussianPro

data_extraction/build_html.py

@@ -643,7 +643,7 @@ def get_plot_data(ranks):
 
     checkbox_states = {}
     for method in shortnames.values():
-        if method in ["Scaffold-GS", "AtomGS"]:
+        if method in ["Scaffold-GS", "AtomGS", "GaussianPro"]:
             checkbox_states[method] = False
         else:
             checkbox_states[method] = True

data_extraction/data_extraction.py

@@ -209,7 +209,7 @@ def read_csvs(sources_file):
                         print('Downloaded', dataset)
                         data = StringIO(table)
                         df = pd.read_csv(data,dtype={
-                            'Size [Bytes]': 'Int64',
+                            'Size [Bytes]': 'float',
                         })
                         df['Submethod'] = df['Submethod'].apply(lambda x: '' if isinstance(x, str) and x.strip() == '' else x) # make empty submethod names empty
                         df['Submethod'] = df['Submethod'].apply(lambda x: ' ' + x if isinstance(x, str) and len(x)>0 and x != "Baseline" and x[0].isalpha() else x) #add space if starts with alphabetical character

data_extraction/data_source.yaml

@@ -51,4 +51,8 @@ wu2024implicit:
 
 xie2024mesongs:
   url: "https://github.com/ShuzhaoXie/MesonGS/tree/main/results"
+  is_csv: True
+
+cheng2024gaussianpro:
+  url: "https://github.com/kcheng1021/GaussianPro/tree/version1.0/results"
   is_csv: True

methods_densification.bib

@@ -35,7 +35,7 @@ @misc{cheng2024gaussianpro
       eprint={2402.14650},
       archivePrefix={arXiv},
       primaryClass={cs.CV},
-      url={https://arxiv.org/abs/2402.14650}, 
+      url={https://kcheng1021.github.io/gaussianpro.github.io/}, 
       shortname = {GaussianPro}
 }
 @misc{zhang2024fregs,

results/DeepBlending.csv

@@ -4,6 +4,8 @@ chen2024hac,,30.14,0.903,0.265,4917821,,https://arxiv.org/pdf/2403.14530,
 chen2024hac,,30.17,0.905,0.262,5578424,,https://arxiv.org/pdf/2403.14530,
 chen2024hac,-highrate,30.34,0.906,0.258,6658457,,https://arxiv.org/src/2403.14530,==λ1e-3
 chen2024hac,,30.21,0.906,0.257,7948206,,https://arxiv.org/pdf/2403.14530,
+cheng2024gaussianpro,,29.84,0.912,0.225,607571149,2449878.0,https://raw.githubusercontent.com/kcheng1021/GaussianPro/version1.0/results,
+cheng2024gaussianpro,Baseline,29.79,0.913,0.222,640517407,2582735.0,https://raw.githubusercontent.com/kcheng1021/GaussianPro/version1.0/results,
 fan2024lightgaussian,,,,,,,,
 fang2024minisplatting,Baseline,29.98,0.908,0.253,,350000.0,https://arxiv.org/pdf/2403.14166,
 fang2024minisplatting,-D,29.88,0.906,0.211,,4630000.0,https://arxiv.org/pdf/2403.14166,
@@ -20,6 +22,8 @@ navaneet2023compact3d, 32K,29.90,0.907,0.251,13631488,554000.0,https://arxiv.org
 niedermayr2024compressed,Baseline,29.381,0.898,0.253,26528973,,https://arxiv.org/pdf/2401.02436,
 papantonakis2024reducing,Baseline,29.63,0.902,0.249,18874368,1010000.0,https://repo-sam.inria.fr/fungraph/reduced_3dgs/reduced_3DGS_i3d.pdf,
 ren2024octreegs,Baseline,30.41,0.913,0.238,,144000.0,https://arxiv.org/pdf/2403.17898,
+taming20243dgs,Baseline,27.79,0.822,0.263,,270000.0,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
+taming20243dgs, (Big),30.14,0.907,0.235,,2810000.0,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
 wang2024end,,29.35,0.895,0.277,4135678,318768.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
 wang2024end,,29.49,0.899,0.265,6706772,528719.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
 wang2024end,,29.59,0.902,0.257,10959800,887813.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
@@ -28,5 +32,3 @@ wu2024implicit, low,30.63,0.904,0.293,6647242,1536100.0,https://raw.githubuserco
 wu2024implicit, high,32.33,0.924,0.253,8113732,1536100.0,https://raw.githubusercontent.com/wuminye/ImplicitGS/main/results,
 xie2024mesongs, c3,29.48,0.903,0.252,29011600,2022966.0,https://raw.githubusercontent.com/ShuzhaoXie/MesonGS/main/results,
 xie2024mesongs, c1,29.50,0.903,0.251,31071609,2166331.0,https://raw.githubusercontent.com/ShuzhaoXie/MesonGS/main/results,
-taming20243dgs,Baseline,27.79,0.822,0.263,,270000,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
-taming20243dgs, (Big),30.14,0.907,0.235,,2810000,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,

results/MipNeRF360.csv

@@ -4,6 +4,8 @@ chen2024hac,,27.62,0.808,0.236,17374904,,https://arxiv.org/pdf/2403.14530,
 chen2024hac,,27.72,0.809,0.233,19440599,,https://arxiv.org/pdf/2403.14530,
 chen2024hac,-highrate,27.77,0.811,0.230,22932357,,https://arxiv.org/src/2403.14530,==λ1e-3
 chen2024hac,,27.83,0.811,0.229,26224886,,https://arxiv.org/pdf/2403.14530,
+cheng2024gaussianpro,,27.46,0.813,0.217,750575361,3026509.0,https://raw.githubusercontent.com/kcheng1021/GaussianPro/version1.0/results,
+cheng2024gaussianpro,Baseline,27.43,0.813,0.219,844072223,3403512.0,https://raw.githubusercontent.com/kcheng1021/GaussianPro/version1.0/results,
 fan2024lightgaussian,Baseline,27.28,0.805,0.243,44040192,,https://arxiv.org/src/2311.17245,
 fang2024minisplatting,Baseline,27.34,0.822,0.217,,490000.0,https://arxiv.org/pdf/2403.14166,
 fang2024minisplatting,-D,27.51,0.831,0.176,,4690000.0,https://arxiv.org/pdf/2403.14166,
@@ -16,6 +18,7 @@ hu2024gsplat,,27.70,0.825,0.197,57812682,4000000.0,https://raw.githubusercontent
 kim2024CVPR,Baseline,27.07,0.797,0.249,76546048,646000.0,https://openaccess.thecvf.com/content/CVPR2024W/3DMV/papers/Kim_Color-cued_Efficient_Densification_Method_for_3D_Gaussian_Splatting_CVPRW_2024_paper.pdf,
 lee2024compact,+PP,27.03,0.797,0.247,30513561,,https://arxiv.org/src/2311.13681,
 lee2024compact,Baseline,27.08,0.798,0.247,51170508,1388162.0,https://arxiv.org/src/2311.13681,
+liu2024atomgs,Baseline,27.38,0.816,0.211,778950993,3140929.0,https://arxiv.org/pdf/2405.12369,(#Gaussians and Size in Email to Yi-Hsin)
 lu2024scaffold,Baseline,27.50,0.806,0.252,266233446,,https://arxiv.org/pdf/2403.14530,Results taken from HAC paper as they only evaluated on 7 scenes
 morgenstern2024compact, w/o SH,26.56,0.791,0.241,16684812,2149729.0,https://raw.githubusercontent.com/fraunhoferhhi/Self-Organizing-Gaussians/main/results,
 morgenstern2024compact,Baseline,27.08,0.799,0.230,40284501,2176333.0,https://raw.githubusercontent.com/fraunhoferhhi/Self-Organizing-Gaussians/main/results,
@@ -24,6 +27,8 @@ navaneet2023compact3d, 32K,27.12,0.806,0.240,19922944,845000.0,https://arxiv.org
 niedermayr2024compressed,Baseline,26.981,0.801,0.238,30198989,,https://arxiv.org/pdf/2401.02436,
 papantonakis2024reducing,Baseline,27.10,0.809,0.226,30408704,1460000.0,https://repo-sam.inria.fr/fungraph/reduced_3dgs/reduced_3DGS_i3d.pdf,
 ren2024octreegs,Baseline,27.73,0.815,0.217,,686000.0,https://arxiv.org/pdf/2403.17898,
+taming20243dgs,Baseline,27.29,0.799,0.253,,630000.0,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
+taming20243dgs, (Big),27.79,0.822,0.205,,3310000.0,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
 wang2024end,,26.03,0.764,0.299,6162424,479851.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
 wang2024end,,26.50,0.784,0.268,9761150,776862.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
 wang2024end,,26.87,0.796,0.248,15351860,1237152.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
@@ -32,6 +37,3 @@ wu2024implicit, low,27.34,0.811,0.255,13373397,2092967.0,https://raw.githubuserc
 wu2024implicit, high,27.62,0.820,0.245,27021354,2092967.0,https://raw.githubusercontent.com/wuminye/ImplicitGS/main/results,
 xie2024mesongs, c3,26.99,0.797,0.246,25929623,1870378.0,https://raw.githubusercontent.com/ShuzhaoXie/MesonGS/main/results,
 xie2024mesongs, c1,26.99,0.796,0.247,28484305,2082024.0,https://raw.githubusercontent.com/ShuzhaoXie/MesonGS/main/results,
-taming20243dgs,Baseline,27.29,0.799,0.253,,630000,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
-taming20243dgs, (Big),27.79,0.822,0.205,,3310000,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
-liu2024atomgs,Baseline,27.38,0.816,0.211,778950993,3140929,https://arxiv.org/pdf/2405.12369,(#Gaussians and Size in Email to Yi-Hsin)

results/TanksAndTemples.csv

@@ -4,6 +4,8 @@ chen2024hac,,24.24,0.849,0.183,9122611,,https://arxiv.org/pdf/2403.14530,
 chen2024hac,,24.33,0.850,0.181,10380902,,https://arxiv.org/pdf/2403.14530,
 chen2024hac,-highrate,24.40,0.853,0.177,11785994,,https://arxiv.org/src/2403.14530,==λ1e-3
 chen2024hac,,24.25,0.853,0.176,13799260,,https://arxiv.org/pdf/2403.14530,
+cheng2024gaussianpro,,23.71,0.857,0.186,349679125,1410003.0,https://raw.githubusercontent.com/kcheng1021/GaussianPro/version1.0/results,
+cheng2024gaussianpro,Baseline,24.09,0.862,0.185,357428101,1441225.0,https://raw.githubusercontent.com/kcheng1021/GaussianPro/version1.0/results,
 fan2024lightgaussian,Baseline,23.11,0.817,0.231,23068672,,https://arxiv.org/src/2311.17245,
 fang2024minisplatting,Baseline,23.18,0.835,0.202,,200000.0,https://arxiv.org/pdf/2403.14166,
 fang2024minisplatting,-D,23.23,0.853,0.140,,4280000.0,https://arxiv.org/pdf/2403.14166,
@@ -16,6 +18,7 @@ hu2024gsplat,,24.47,0.872,0.132,58239022,4000000.0,https://raw.githubusercontent
 kim2024CVPR,Baseline,23.18,0.830,0.198,44040192,370000.0,https://openaccess.thecvf.com/content/CVPR2024W/3DMV/papers/Kim_Color-cued_Efficient_Densification_Method_for_3D_Gaussian_Splatting_CVPRW_2024_paper.pdf,
 lee2024compact,+PP,23.32,0.831,0.202,21915238,,https://arxiv.org/src/2311.13681,
 lee2024compact,Baseline,23.32,0.831,0.201,41313894,836296.0,https://arxiv.org/src/2311.13681,
+liu2024atomgs,Baseline,23.70,0.849,0.166,367206072,1480685.0,https://arxiv.org/pdf/2405.12369,(#Gaussians and Size in Email to Yi-Hsin)
 lu2024scaffold,Baseline,23.96,0.853,0.177,91226112,,https://arxiv.org/pdf/2312.00109,
 morgenstern2024compact, w/o SH,23.15,0.828,0.198,9293275,1207490.0,https://raw.githubusercontent.com/fraunhoferhhi/Self-Organizing-Gaussians/main/results,
 morgenstern2024compact,Baseline,23.56,0.837,0.186,22778535,1242209.0,https://raw.githubusercontent.com/fraunhoferhhi/Self-Organizing-Gaussians/main/results,
@@ -25,6 +28,8 @@ niedermayr2024compressed,Baseline,23.324,0.832,0.194,18119393,,https://arxiv.org
 papantonakis2024reducing,Baseline,23.57,0.840,0.188,14680064,680000.0,https://repo-sam.inria.fr/fungraph/reduced_3dgs/reduced_3DGS_i3d.pdf,
 ren2024octreegs,Baseline,24.52,0.866,0.153,,481000.0,https://arxiv.org/pdf/2403.17898,
 sun2024f3dgs,-CP-16,30.29,0.957,0.061,11471421,,https://arxiv.org/pdf/2405.17083,[N/T][N/P]
+taming20243dgs,Baseline,23.89,0.835,0.207,,290000.0,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
+taming20243dgs, (Big),24.04,0.851,0.170,,1840000.0,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
 wang2024end,,22.98,0.812,0.234,3737081,263067.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
 wang2024end,,23.14,0.823,0.215,5492385,395042.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
 wang2024end,,23.28,0.831,0.202,8017022,597209.0,https://raw.githubusercontent.com/USTC-IMCL/RDO-Gaussian/main/results,
@@ -33,6 +38,3 @@ wu2024implicit, low,23.70,0.836,0.227,8852922,1278063.0,https://raw.githubuserco
 wu2024implicit, high,24.05,0.849,0.211,13143920,1278063.0,https://raw.githubusercontent.com/wuminye/ImplicitGS/main/results,
 xie2024mesongs, c3,23.29,0.835,0.197,17357031,1162500.0,https://raw.githubusercontent.com/ShuzhaoXie/MesonGS/main/results,
 xie2024mesongs, c1,23.31,0.835,0.196,18465486,1239197.0,https://raw.githubusercontent.com/ShuzhaoXie/MesonGS/main/results,
-taming20243dgs,Baseline,23.89,0.835,0.207,,290000,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
-taming20243dgs, (Big),24.04,0.851,0.170,,1840000,https://humansensinglab.github.io/taming-3dgs/docs/paper.pdf,
-liu2024atomgs,Baseline,23.70,0.849,0.166,367206072,1480685,https://arxiv.org/pdf/2405.12369,(#Gaussians and Size in Email to Yi-Hsin)