Last year, we showed how to turn Stable Diffusion 2 into a SOTA depth estimator with a few synthetic samples and 2–3 days on just 1 GPU.
Today's release features:
🏎️ 1-step inference
🔢 New modalities
🫣 High resolution
🧨 Diffusers support
🕹️ New demos
🧶👇
Last year, we showed how to turn Stable Diffusion 2 into a SOTA depth estimator with a few synthetic samples and 2–3 days on just 1 GPU.
Today's release features:
🏎️ 1-step inference
🔢 New modalities
🫣 High resolution
🧨 Diffusers support
🕹️ New demos
🧶👇
Last year, we showed how to turn Stable Diffusion 2 into a SOTA depth estimator with a few synthetic samples and 2–3 days on just 1 GPU.
Today's release features:
🏎️ 1-step inference
🔢 New modalities
🫣 High resolution
🧨 Diffusers support
🕹️ New demos
🧶👇
Site: sites.google.com/view/iccv25t...
Codalab: codalab.lisn.upsaclay.fr/competitions...
Site: sites.google.com/view/iccv25t...
Codalab: codalab.lisn.upsaclay.fr/competitions...
careers.huaweirc.ch/jobs/5702605...
careers.huaweirc.ch/jobs/5702605...
🚀 Dev phase: Feb 1 - Mar 1
🎯 Final phase: Mar 1 - Mar 21
Website: jspenmar.github.io/MDEC/
🌐 Codalab: codalab.lisn.upsaclay.fr/competitions...
Bring your best depth!
🚀 Dev phase: Feb 1 - Mar 1
🎯 Final phase: Mar 1 - Mar 21
Website: jspenmar.github.io/MDEC/
🌐 Codalab: codalab.lisn.upsaclay.fr/competitions...
Bring your best depth!
🎉 Website is LIVE: jspenmar.github.io/MDEC/
🎉 Keynotes: Peter Wonka, Yiyi Liao, and Konrad Schindler
🎉 Challenge updates: new prediction types, baselines & metrics
🎉 Website is LIVE: jspenmar.github.io/MDEC/
🎉 Keynotes: Peter Wonka, Yiyi Liao, and Konrad Schindler
🎉 Challenge updates: new prediction types, baselines & metrics
A method for mining 4D from internet stereo videos. It enables large-scale, high-quality, dynamic, *metric* 3D reconstructions, with camera poses and long-term 3D motion trajectories.
We used Stereo4D to make a dataset of over 100k real-world 4D scenes.
A method for mining 4D from internet stereo videos. It enables large-scale, high-quality, dynamic, *metric* 3D reconstructions, with camera poses and long-term 3D motion trajectories.
We used Stereo4D to make a dataset of over 100k real-world 4D scenes.
But it takes exceptional artistic skills to make one.
We present Illusion3D - a simple method for creating 3D multiview illusions, where the interpretations change depending on your perspectives.
Let's play Where's Waldo, shall we? 😆
But it takes exceptional artistic skills to make one.
We present Illusion3D - a simple method for creating 3D multiview illusions, where the interpretations change depending on your perspectives.
Let's play Where's Waldo, shall we? 😆
For more stable and detailed metric depth, I solve for the per-frame affine transform that optimally "anchors" the monodepth to the LiDAR.
youtube.com/shorts/u3OVj...
For more stable and detailed metric depth, I solve for the per-frame affine transform that optimally "anchors" the monodepth to the LiDAR.
youtube.com/shorts/u3OVj...
Soon, there might (or might not) be a Marigold framework that solves this problem👀
Time to have a coffee ☕️ and update all the AI starter packs 🥹
Time to have a coffee ☕️ and update all the AI starter packs 🥹