wanmeihuali / taichi_3d_gaussian_splatting

An unofficial implementation of paper 3D Gaussian Splatting for Real-Time Radiance Field Rendering by taichi lang.
Apache License 2.0
637 stars 58 forks source link

Support grad for depth only in rasterizer #122

Open wanmeihuali opened 10 months ago

github-actions[bot] commented 10 months ago

Running experiment on sagemaker with git sha 7e2e1f2d2f819a6908941292549e771dac3f21da

github-actions[bot] commented 10 months ago

Training job grad-depth-7e2e1f2-230909-005041-tat-truck-baseline created

github-actions[bot] commented 10 months ago

Running experiment on sagemaker with git sha 7e2e1f2d2f819a6908941292549e771dac3f21da

github-actions[bot] commented 10 months ago

Training job grad-depth-7e2e1f2-230909-005149-tat-train-baseline created

github-actions[bot] commented 10 months ago

Training job grad-depth-7e2e1f2-230909-005041-tat-truck-baseline completed.

Model url: s3://taichi-3d-gaussian-splatting-log/tat-truck-baseline/grad-depth-7e2e1f2-230909-005041-tat-truck-baseline/output/model.tar.gz,

tensorboard output path: s3://taichi-3d-gaussian-splatting-log/tat-truck-baseline/grad-depth-7e2e1f2-230909-005041-tat-truck-baseline/output/output.tar.gz

github-actions[bot] commented 10 months ago

Training job grad-depth-7e2e1f2-230909-005041-tat-truck-baseline final metrics:

Latest Metrics

train:iteration train:l1loss train:loss train:num_valid_points train:psnr train:ssim train:ssimloss val:loss val:psnr val:ssim
30000.0 0.02365143597126007 0.04058298096060753 442217.0 27.55559730529785 0.8916908502578735 0.10830914974212646 0.05380209535360336 25.163917541503906 0.8650290369987488

Max Metrics

train:5kpsnr train:5kssim train:7kpsnr train:7kssim train:psnr train:ssim val:5kpsnr val:5kssim val:7kpsnr val:7kssim val:psnr val:ssim
24.77243423461914 0.8409563302993774 24.086151123046875 0.8653521537780762 27.55559730529785 0.8916908502578735 23.030521392822266 0.8133056163787842 23.853111267089844 0.8373969197273254 25.163917541503906 0.8650290369987488
github-actions[bot] commented 10 months ago

Training job grad-depth-7e2e1f2-230909-005149-tat-train-baseline completed.

Model url: s3://taichi-3d-gaussian-splatting-log/tat-train-baseline/grad-depth-7e2e1f2-230909-005149-tat-train-baseline/output/model.tar.gz,

tensorboard output path: s3://taichi-3d-gaussian-splatting-log/tat-train-baseline/grad-depth-7e2e1f2-230909-005149-tat-train-baseline/output/output.tar.gz

github-actions[bot] commented 10 months ago

Training job grad-depth-7e2e1f2-230909-005149-tat-train-baseline final metrics:

Latest Metrics

train:iteration train:l1loss train:loss train:num_valid_points train:psnr train:ssim train:ssimloss val:loss val:psnr val:ssim
30000.0 0.027597062289714813 0.041713614016771317 677702.0 26.506502151489258 0.901820182800293 0.09817981719970703 0.09981270134449005 20.97577476501465 0.801036536693573

Max Metrics

train:5kpsnr train:5kssim train:7kpsnr train:7kssim train:psnr train:ssim val:5kpsnr val:5kssim val:7kpsnr val:7kssim val:psnr val:ssim
18.4986572265625 0.740445613861084 19.621097564697266 0.780716061592102 26.506502151489258 0.901820182800293 18.968416213989258 0.7297627329826355 19.654048919677734 0.7564723491668701 20.97577476501465 0.801036536693573
github-actions[bot] commented 10 months ago

Running experiment on sagemaker with git sha 85724d7bc0632f3ab7a66b0c8cd01f0b4f98bb57

github-actions[bot] commented 10 months ago

Training job grad-depth-85724d7-230910-044828-tat-truck-baseline created

github-actions[bot] commented 10 months ago

Running experiment on sagemaker with git sha 85724d7bc0632f3ab7a66b0c8cd01f0b4f98bb57

github-actions[bot] commented 10 months ago

Training job grad-depth-85724d7-230910-044944-tat-train-baseline created

github-actions[bot] commented 10 months ago

Training job grad-depth-85724d7-230910-044828-tat-truck-baseline completed.

Model url: s3://taichi-3d-gaussian-splatting-log/tat-truck-baseline/grad-depth-85724d7-230910-044828-tat-truck-baseline/output/model.tar.gz,

tensorboard output path: s3://taichi-3d-gaussian-splatting-log/tat-truck-baseline/grad-depth-85724d7-230910-044828-tat-truck-baseline/output/output.tar.gz

github-actions[bot] commented 10 months ago

Training job grad-depth-85724d7-230910-044828-tat-truck-baseline final metrics:

Latest Metrics

train:iteration train:l1loss train:loss train:num_valid_points train:psnr train:ssim train:ssimloss val:loss val:psnr val:ssim
30000.0 0.035545192658901215 0.059377893805503845 439447.0 23.571882247924805 0.8452913165092468 0.15470868349075317 0.05419863015413284 25.105846405029297 0.8648907542228699

Max Metrics

train:5kpsnr train:5kssim train:7kpsnr train:7kssim train:psnr train:ssim val:5kpsnr val:5kssim val:7kpsnr val:7kssim val:psnr val:ssim
22.985036849975586 0.81522536277771 23.676334381103516 0.8425229787826538 23.571882247924805 0.8452913165092468 23.084001541137695 0.8149509429931641 23.93067169189453 0.838331937789917 25.105846405029297 0.8648907542228699
github-actions[bot] commented 10 months ago

Training job grad-depth-85724d7-230910-044944-tat-train-baseline completed.

Model url: s3://taichi-3d-gaussian-splatting-log/tat-train-baseline/grad-depth-85724d7-230910-044944-tat-train-baseline/output/model.tar.gz,

tensorboard output path: s3://taichi-3d-gaussian-splatting-log/tat-train-baseline/grad-depth-85724d7-230910-044944-tat-train-baseline/output/output.tar.gz

github-actions[bot] commented 10 months ago

Training job grad-depth-85724d7-230910-044944-tat-train-baseline final metrics:

Latest Metrics

train:iteration train:l1loss train:loss train:num_valid_points train:psnr train:ssim train:ssimloss val:loss val:psnr val:ssim
30000.0 0.04131251946091652 0.06635285913944244 668398.0 23.763450622558594 0.8334857821464539 0.16651421785354614 0.09747117757797241 21.061948776245117 0.8045176267623901

Max Metrics

train:5kpsnr train:5kssim train:7kpsnr train:7kssim train:psnr train:ssim val:5kpsnr val:5kssim val:7kpsnr val:7kssim val:psnr val:ssim
22.968643188476562 0.8369643688201904 22.771406173706055 0.8545178174972534 23.763450622558594 0.8334857821464539 19.088722229003906 0.731535017490387 19.672351837158203 0.7568982243537903 21.061948776245117 0.8045176267623901