Unsupervised Object Segmentation

8 papers with code • 3 benchmarks • 4 datasets

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Greatest papers with code

Multi-Object Representation Learning with Iterative Variational Inference

deepmind/deepmind-research 1 Mar 2019

Human perception is structured around objects which form the basis for our higher-level cognition and impressive systematic generalization abilities.

Representation Learning Systematic Generalization +2

Unsupervised Object Segmentation by Redrawing

mickaelChen/ReDO NeurIPS 2019

Object segmentation is a crucial problem that is usually solved by using supervised learning approaches over very large datasets composed of both images and corresponding object masks.

Semantic Segmentation Unsupervised Object Segmentation

MONet: Unsupervised Scene Decomposition and Representation

deepmind/multi_object_datasets 22 Jan 2019

The ability to decompose scenes in terms of abstract building blocks is crucial for general intelligence.

Latent Variable Models Object Discovery +1

Object Segmentation Without Labels with Large-Scale Generative Models

anvoynov/BigGANsAreWatching 8 Jun 2020

The recent rise of unsupervised and self-supervised learning has dramatically reduced the dependency on labeled data, providing effective image representations for transfer to downstream vision tasks.

Image Classification Saliency Detection +3

GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement

applied-ai-lab/genesis 20 Apr 2021

Moreover, object representations are often inferred using RNNs which do not scale well to large images or iterative refinement which avoids imposing an unnatural ordering on objects in an image but requires the a priori initialisation of a fixed number of object representations.

Image Generation Latent Variable Models +4

Emergence of Object Segmentation in Perturbed Generative Models

adambielski/perturbed-seg NeurIPS 2019

To force the generator to learn a representation where the foreground layer corresponds to an object, we perturb the output of the generative model by introducing a random shift of both the foreground image and mask relative to the background.

Semantic Segmentation Unsupervised Object Segmentation

Object Discovery with a Copy-Pasting GAN

basilevh/object-discovery-cp-gan 27 May 2019

We tackle the problem of object discovery, where objects are segmented for a given input image, and the system is trained without using any direct supervision whatsoever.

Object Discovery Unsupervised Object Segmentation