Vector Neurons We introduce a general framework built on top of what we call Vector Neurons for creating SO(3) equivariant neural networks. Extending neurons from single scalars to 3D vectors, our vector neurons transport SO(3) actions to latent spaces and provide a framework for building equivariance in common neural operations including linear layers, non-linearities, pooling, and normalization. Created by Congyue Deng, Or Litany, Yueqi Duan, Adrien Poulenard, Andrea Tagliasacchi, and Leonidas Guibas. Overview vnn is the author’s implementation of Vector […]

Scene Graph Benchmark in PyTorch 1.4 This project aims at providing the necessary building blocks for easily creating detection and segmentation models using PyTorch 1.0. Highlights Upgrad to pytorch 1.4 (can also upgrade to 1.7) Multi-GPU training and inference Batched inference: can perform inference using multiple images per batch per GPU. Fast and flexible tsv dataset format Remove FasterRCNN detector dependency: during relation head training, can plugin bounding boxes from any detector. Provides pre-trained models for different scene graph detection […]

few-shot-gan-adaptation Official repository for Few-shot Image Generation via Cross-domain Correspondence (CVPR ’21) Utkarsh Ojha, Yijun Li, Jingwan Lu, Alexei A. Efros, Yong Jae Lee, Eli Shechtman, Richard Zhang Adobe Research, UC Davis, UC Berkeley Repository for downloading the datasets and generated images used for performing the evaluations shown in Tables 1 and 2. Overview Our method helps adapt the source GAN where one-to-one correspondence is preserved between the source Gs(z) and target Gt(z) images. Sample images from a model To […]