3D scene generation is a very exciting direction and hope this paper could contribute to it! It is really amazing to work with Lukas Höllein Andrew Owens Matthias Niessner Justin Johnson

Excited for the release of our new Flythroughs app. Take a video with the app to turn it into a cinematic drone flythrough video using NeRF technology. Luma AI #NeRFs #3D #AI lumalabs.ai/flythroughs

Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesis dynamic3dgaussians.github.io We model the world as a set of 3D Gaussians that move & rotate over time. This extends Gaussian Splatting to dynamic scenes, with accurate novel-view synthesis and dense 3D trajectories.

Annotator disagreement is common in NLP, but is it just noise? We are introducing a new strategy for annotator representation to help models better learn from data that has inherent disagreements. 🐙 Github code: github.com/MichiganNLP/An…

This is so cool!!

📢 Introducing AffordanceLLM We aim to enhance the generalization capability of affordance grounding to in-the-wild objects that are unseen during training, by developing a new approach AffordanceLLM, that takes the advantage of the rich knowledge from large-scale VLMs.

📢 Presenting 𝐅𝐀𝐑: 𝐅𝐥𝐞𝐱𝐢𝐛𝐥𝐞, 𝐀𝐜𝐜𝐮𝐫𝐚𝐭𝐞 𝐚𝐧𝐝 𝐑𝐨𝐛𝐮𝐬𝐭 𝟔𝐃𝐨𝐅 𝐑𝐞𝐥𝐚𝐭𝐢𝐯𝐞 𝐂𝐚𝐦𝐞𝐫𝐚 𝐏𝐨𝐬𝐞 𝐄𝐬𝐭𝐢𝐦𝐚𝐭𝐢𝐨𝐧 #CVPR2024 FAR builds upon complimentary Solver and Learning-Based works yielding accurate *and* robust pose! crockwell.github.io/far/

What do you see in these images? These are called hybrid images, originally proposed by Aude Oliva et al. They change appearance depending on size or viewing distance, and are just one kind of perceptual illusion that our method, Factorized Diffusion, can make.

Really cool work!

At #CVPR2024: Tactile-augmented Radiance Fields! We probe a scene with a touch sensor and localize each sample within a NeRF. We use diffusion to estimate the tactile signals for the points we didn't touch. x.com/_yimingdou/sta… w/ Yiming Dou, Antonio Loquercio, Fengyu Yang, Yi Liu

These spectrograms look like images, but can also be played as a sound! We call these images that sound. How do we make them? Look and listen below to find out, and to see more examples!