23 citations · 30 across the 4 of their papers we have counts for
4 papers
CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos
Nikita Karaev, Iurii Makarov, Jianyuan Wang +3
Most state-of-the-art point trackers are trained on synthetic data due to the difficulty of annotating real videos for this task. However, this can result in suboptimal performance…
Meta 3D Gen
Raphael Bensadoun, Tom Monnier, Yanir Kleiman +17
We introduce Meta 3D Gen (3DGen), a new state-of-the-art, fast pipeline for text-to-3D asset generation. 3DGen offers 3D asset creation with high prompt fidelity and high-quality 3…
Real-time volumetric rendering of dynamic humans
Ignacio Rocco, Iurii Makarov, Filippos Kokkinos +4
We present a method for fast 3D reconstruction and real-time rendering of dynamic humans from monocular videos with accompanying parametric body fits. Our method can reconstruct a…
Text-To-4D Dynamic Scene Generation
Uriel Singer, Shelly Sheynin, Adam Polyak +8
We present MAV3D (Make-A-Video3D), a method for generating three-dimensional dynamic scenes from text descriptions. Our approach uses a 4D dynamic Neural Radiance Field (NeRF), whi…