by Stanford University · 0 reviews
A deep learning architecture for directly processing point clouds without converting to regular grids, used for 3D object classification and segmentation.
by UC Berkeley · 0 reviews
An open-source framework for neural radiance field development providing plug-and-play components for NeRF-based 3D reconstruction from images.
by NVIDIA · 0 reviews
A framework for neural graphics primitives enabling fast training and rendering of neural radiance fields using learned hash tables.
by Google Research · 0 reviews
Family of convolutional neural networks that use compound scaling to uniformly scale depth, width, and resolution for efficient image classification.
by Google Research · 0 reviews
Deep convolutional neural network trained on ImageNet for classifying images into object categories with high accuracy.
by Google Research · 0 reviews
Applies transformers directly to image patches for classification; inspired many CV variants.
by Meta AI · 0 reviews
A promptable zero-shot image segmentation model trained on 1.1B masks over 11M images.