Interesting and smart application. Accurate counting can be done only in 3D space for fruit trees and something similar…

Messing around with the new Flux Controlnet Depth model

And can make the training significantly faster with #InstantSplat 🫣

finally ranked as CCF-A

Excellent work on creating a smooth interface that enables straightforward comparisons! It would be beneficial to include FPS (frames per second) as a major metric, given that redundancy removal of Gaussians typically enhances rendering speed. We have recently extended

Glad to see our CasMVSNet is wildly used, it proposes the cascade and efficient cost volume formulation

Put this into VR/AR glasses 🕶️

What is a really really hard problem to work on in #AI? My own answer is Spatial Intelligence - a technology that could empower and enable countless possible use cases in creation, design, learning, AR/VR, robotics, and beyond. It’s a real honor that my cofounders Justin Johnson

Cheers

Thanks for posting it!

Excellent flowchart.

Amazing to see the work of Prof. Achuta Kadambi showcasing the power of computer vision to predict a heartbeat from just a video of a face! It feels like magic. Pepperdine University UCLA Samueli Engineering #digitaltwin #computervision

#ECCV2024 is happening soon in Milan! Unfortunately, many collaborators are unable to attend due to visa issues, but we’re making sure everything is ready ahead of time! (1/3) We’re excited to announce the release of our DreamScene360 code: dreamscene360.github.io. With it, you

This week we will be presenting 3 papers European Conference on Computer Vision #ECCV2024, on online mapping (Boris Ivanovic), traffic scenario generation, and VLM-based AV stacks (Chaowei Xiao): Paper 1: arxiv.org/pdf/2407.06683 Paper 2: arxiv.org/abs/2312.13303 Paper 3: vlm-driver.github.io More on online mapping 👇

Awesome, we are doing similar things but shall all embed foundation model prior to perfect dense 3d reconstruction