Object-Centric Learning with Slot Attention

Last update: Jan 02, 2023

Related tags

Overview

Slot Attention

This is a re-implementation of "Object-Centric Learning with Slot Attention" in PyTorch (https://arxiv.org/abs/2006.15055).

Requirements

Poetry
Python >= 3.8
PyTorch >= 1.7.1
Pytorch Lightning >= 1.1.4
CUDA enabled computing device

Note: the model was run using a Nvidia Tesla V100 16GB GPU.

Getting Started

Run run.sh to get started. This script will install the dependencies, download the CLEVR dataset and run the model.

Usage

python slot_attention/train.py

Modify SlotAttentionParams in slot_attention/train.py to modify the hyperparameters. See slot_attenion/params.py for the default hyperparamters.

Logging

To log outputs to wandb, run wandb login YOUR_API_KEY and set is_logging_enabled=True in SlotAttentionParams.

Acknowledgements

Special thanks to the original authors of the paper: Francesco Locatello, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, and Thomas Kipf.

Owner

Untitled AI

We're investigating the fundamentals of learning across humans and machines in order to create more general machine intelligence.

GitHub Repository

External Attention Network

Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks paper : https://arxiv.org/abs/2105.02358 EAMLP will come soon Jitto

357 Dec 11, 2022

Code for the CVPR2021 workshop paper "Noise Conditional Flow Model for Learning the Super-Resolution Space"

NCSR: Noise Conditional Flow Model for Learning the Super-Resolution Space Official NCSR training PyTorch Code for the CVPR2021 workshop paper "Noise

57 Oct 03, 2022

This is a clean and robust Pytorch implementation of DQN and Double DQN.

DQN/DDQN-Pytorch This is a clean and robust Pytorch implementation of DQN and Double DQN. Here is the training curve: All the experiments are trained

15 Dec 27, 2022

Official code repository of the paper Learning Associative Inference Using Fast Weight Memory by Schlag et al.

Learning Associative Inference Using Fast Weight Memory This repository contains the offical code for the paper Learning Associative Inference Using F

18 Oct 12, 2022

Tool for working with Y-chromosome data from YFull and FTDNA

ycomp ycomp is a tool for working with Y-chromosome data from YFull and FTDNA. Run ycomp -h for information on how to use the program. Installation Th

2 Jun 18, 2022

Build tensorflow keras model pipelines in a single line of code. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.

deep_autoviml Build keras pipelines and models in a single line of code! Table of Contents Motivation How it works Technology Install Usage API Image

102 Dec 17, 2022

Space-event-trace - Tracing service for spaceteam events

space-event-trace Tracing service for TU Wien Spaceteam events. This service is

2 Jan 04, 2022

Deep Residual Networks with 1K Layers

Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc

856 Jan 06, 2023

Official Code for AdvRush: Searching for Adversarially Robust Neural Architectures (ICCV '21)

AdvRush Official Code for AdvRush: Searching for Adversarially Robust Neural Architectures (ICCV '21) Environmental Set-up Python == 3.6.12, PyTorch =

11 Dec 10, 2022

Code release for Local Light Field Fusion at SIGGRAPH 2019

Local Light Field Fusion Project | Video | Paper Tensorflow implementation for novel view synthesis from sparse input images. Local Light Field Fusion

1.1k Dec 27, 2022

StyleGAN-Human: A Data-Centric Odyssey of Human Generation

StyleGAN-Human: A Data-Centric Odyssey of Human Generation Abstract: Unconditional human image generation is an important task in vision and graphics,

762 Jan 08, 2023

Automatic Image Background Subtraction

Automatic Image Background Subtraction This repo contains set of scripts for automatic one-shot image background subtraction task using the following

6 Dec 05, 2022

Efficient neural networks for analog audio effect modeling

micro-TCN Efficient neural networks for audio effect modeling

94 Dec 29, 2022

atmaCup #11 の Public 4th / Pricvate 5th Solution のリポジトリです。

#11 atmaCup 2021-07-09 ~ 2020-07-21 に行われた #11 [初心者歓迎! / 画像編] atmaCup のリポジトリです。結果は Public 4th / Private 5th でした。フレームワークは PyTorch で、実装は pytorch-image-m

12 Apr 07, 2022

MLP-Like Vision Permutator for Visual Recognition (PyTorch)

Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition (arxiv) This is a Pytorch implementation of our paper. We present Vision

162 Nov 28, 2022

Implement of "Training deep neural networks via direct loss minimization" in PyTorch for 0-1 loss

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

1 Jan 18, 2022

Code for Mesh Convolution Using a Learned Kernel Basis

Mesh Convolution This repository contains the implementation (in PyTorch) of the paper FULLY CONVOLUTIONAL MESH AUTOENCODER USING EFFICIENT SPATIALLY

35 Jan 03, 2023

Several simple examples for popular neural network toolkits calling custom CUDA operators.

Neural Network CUDA Example Several simple examples for neural network toolkits (PyTorch, TensorFlow, etc.) calling custom CUDA operators. We provide

798 Jan 01, 2023

This repo is the official implementation of "L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization".

L2ight is a closed-loop ONN on-chip learning framework to enable scalable ONN mapping and efficient in-situ learning. L2ight adopts a three-stage learning flow that first calibrates the complicated p

9 Jul 14, 2022

Official implementation of "Learning Proposals for Practical Energy-Based Regression", 2021.

ebms_proposals Official implementation (PyTorch) of the paper: Learning Proposals for Practical Energy-Based Regression, 2021 [arXiv] [project]. Fredr

10 Oct 22, 2022