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This looks super super! Feels like walking into an image!

PhysDreamer Physics-Based Interaction with 3D Objects via Video Generation Realistic object interactions are crucial for creating immersive virtual experiences, yet synthesizing realistic 3D object dynamics in response to novel interactions remains a significant

3D Gaussian is great, but how can you interact with it 🌹👋? Introducing #PhysDreamer: Create your own realistic interactive 3D assets from only static images! Discover how we do this below👇 🧵1/: Website: physdreamer.github.io

I’ll be at #ICLR2024 Vienna during May 7-11! Come and check out our paper! Happy to chat about anything! Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape. Poster on May 9 at 10:45am.

Check out our Generative Camera Dolly🎥 tl;dr: fine-tuning a video model for novel view synthesis of dynamic scenes.

I'm at #CVPR2024 Seattle this week. Happy to chat about anything! Please come and visit our ReconFusion poster on Friday 21 Jun 10:30 a.m, Arch 4A-E Poster #193. reconfusion.github.io

At #ECCV2024, we presented Minimalist Vision with Freeform Pixels, a new vision paradigm that uses a small number of freeform pixels to solve lightweight vision tasks. We are honored to have received the Best Paper Award! Check out the project here: cave.cs.columbia.edu/projects/categ…

CAT4D. The time has come.

Stop watching videos, start interacting with worlds. Stoked to share CAT4D, our new method for turning videos into dynamic 3D scenes that you can move through in real-time!

Check out our new paper that turns (text, sparse images, videos) => (dynamic 3D scenes)! I can't get over how cool the interactive demo is. Try it out for yourself on the project page: cat-4d.github.io

Woohoo, big congrats to the World Labs team! Tech looks similar to CAT3D (cat3d.github.io): multi-view diffusion model + 3DGS, maybe w/360 data + depth priors. To bring these worlds to life with dynamics, check out our new work on CAT4D: cat-4d.github.io 😺

A common question nowadays: Which is better, diffusion or flow matching? 🤔 Our answer: They’re two sides of the same coin. We wrote a blog post to show how diffusion models and Gaussian flow matching are equivalent. That’s great: It means you can use them interchangeably.

Introducing MegaSaM! 🎥 Accurate, fast, & robust structure + camera estimation from casual monocular videos of dynamic scenes! MegaSaM outputs camera parameters and consistent video depth, scaling to long videos with unconstrained camera paths and complex scene dynamics!

How to perform robust 3D reconstruction in the presence of various inconsistencies during capture (e.g., dynamic or lighting changes)? Checkout Alex Trevithick 's SimVS --- simulating the world inconsistencies using video generation models for robust view synthesis!

Introducing 👀Stereo4D👀 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.

Very impressive large-scale 3D scene generation results!!!

⚡️ Introducing Bolt3D ⚡️ Bolt3D generates interactive 3D scenes in less than 7 seconds on a single GPU from one or more images. It features a latent diffusion model that *directly* generates 3D Gaussians of seen and unseen regions, without any test time optimization. 🧵👇 (1/9)

Super cool results! Congrats!