Object-Centric Learning with Slot Attention

Related tags

Deep Learning slot_attention
Overview

Slot Attention

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

Outputs of our slot attention model. This image demonstrates the models ability to divide objects (or parts of objects) into slots.

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.

Comments
  • Is it a bug that `slot_mu` and `slot_log_sigma` is not updated in training?

    Is it a bug that `slot_mu` and `slot_log_sigma` is not updated in training?

    Hi. Thank you for opening source this wonderful implementation! I have a small question about a code and think it might be a bug.

    In these lines, you define slot_mu and slot_log_sigma using register_buffer. If I understand correctly, tensors created via register_buffer won't be updated during training (see here for reference). I also check my trained checkpoints, these two values are indeed the same throughout the training process.

    Also, in other slot-attention implementations, they define them as trainable parameters (see PyTorch one and the official one). So I just wonder if this is a bug or intentional behavior?

    Update: I didn't observe much performance difference using trainable or fixed mu+sigma. That's very interesting.

    opened by Wuziyi616 2
  • How would you save the predicted slots?

    How would you save the predicted slots?

    Great code! I like how it trains on CLEVR out of the box. I would like to save the predicted images like below. Could you help me find out where I could add the Image.save function to get this output? Thanks! image

    opened by IssamLaradji 1
  • Question about the object-centric representation of each slot

    Question about the object-centric representation of each slot

    Maybe this is not the right place to ask this question, but I would like to initiate a discussion about the thing puzzling me when reading the paper.

    My question is: In the paper, the author does not explicitly enforce each slot to represent exactly a single object, then why did not the network learn to use each slot for more than 1 object in the image reconstruction task? Is there any inductive bias imposed by the architecture itself?

    opened by lehduong 0
  • ModuleNotFoundError

    ModuleNotFoundError

    Hi, I am trying to run the slot_attention/train.py code in your repository, however, I keep getting stuck by a error reading...

    Traceback (most recent call last):
  File "slot_attention/train.py", line 8, in <module>
    from slot_attention.data import CLEVRDataModule
ModuleNotFoundError: No module named 'slot_attention'

    I cloned the git to a PC running on the Ubuntu operating system, and upon doing so, I ran the code within the highest directory of the cloned repository, as written in the Readme. Could you help me out with this issue?

    opened by EYUJin 4
  • Testing code

    Testing code

    Hi, thank you very much for the really nice implementation! I have trained the model for 100 epochs and the evaluation results look nice. I was wondering if there's also testing code available. I implemented my own, but I get results such as the image below.

    Thank you very much for your reply.

    123

    opened by ozzyou 14
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