Unsupervised Object Segmentation

Description from the archive archive 2025-07-28; Papers-with-Code links inside it are rewritten to this site.

Benchmarks archive 2025-07-28

9 leaderboard tables shown for this task, 9 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

11 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

23 shown of 23 papers with code (39 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Multi-Object Representation Learning with Iterative Variational Inference
  1 Mar 2019 6 repositories listed Syntology ran 1 of 6 samples · 5 unverified
  Human perception is structured around objects which form the basis for our higher-level cognition and impressive systematic generalization abilities.
• MONet: Unsupervised Scene Decomposition and Representation
  22 Jan 2019 5 repositories listed Syntology ran 1 of 7 samples · 6 unverified
  The ability to decompose scenes in terms of abstract building blocks is crucial for general intelligence.
• Unsupervised Image Decomposition with Phase-Correlation Networks
  7 Oct 2021 2 repositories listed
  The ability to decompose scenes into their object components is a desired property for autonomous agents, allowing them to reason and act in their surroundings.
• GENESIS-V2: Inferring Unordered Object Representations without Iterative Refinement
  20 Apr 2021 2 repositories listed
  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…
• GENESIS: Generative Scene Inference and Sampling with Object-Centric Latent Representations
  30 Jul 2019 2 repositories listed
  Generative latent-variable models are emerging as promising tools in robotics and reinforcement learning.
• MOD-UV: Learning Mobile Object Detectors from Unlabeled Videos
  23 May 2024 1 repository listed Syntology ran 7 of 7 samples · 0 unverified
  As such, prior work has looked at unsupervised instance detection and segmentation, but in the absence of annotated boxes, it is unclear how pixels must be grouped into objects and which objects are of interest.
• Benchmarking and Analysis of Unsupervised Object Segmentation from Real-world Single Images
  8 Dec 2023 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  We first introduce seven complexity factors to quantitatively measure the distributions of background and foreground object biases in appearance and geometry for datasets with human annotations.
• SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers
  1 Dec 2023 1 repository listed Syntology ran 6 of 7 samples · 1 unverified
  Unsupervised object-centric learning aims to decompose scenes into interpretable object entities, termed slots.
• Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping
  17 Apr 2023 1 repository listed
  The Gestalt law of common fate, i.
• DeepCut: Unsupervised Segmentation using Graph Neural Networks Clustering
  12 Dec 2022 1 repository listed Syntology ran 4 of 8 samples · 4 unverified
  This direct connection between the raw features and the clustering objective enables us to implicitly perform classification of the clusters between different graphs, resulting in part semantic segmentation without the…
• ILSGAN: Independent Layer Synthesis for Unsupervised Foreground-Background Segmentation
  25 Nov 2022 1 repository listed
  Unsupervised foreground-background segmentation aims at extracting salient objects from cluttered backgrounds, where Generative Adversarial Network (GAN) approaches, especially layered GANs, show great promise.
• Promising or Elusive? Unsupervised Object Segmentation from Real-world Single Images
  5 Oct 2022 1 repository listed
  We firstly introduce four complexity factors to quantitatively measure the distributions of object- and scene-level biases in appearance and geometry for datasets with human annotations.
• A Simple and Powerful Global Optimization for Unsupervised Video Object Segmentation
  19 Sep 2022 1 repository listed Syntology ran 4 of 10 samples · 6 unverified
  We propose a simple, yet powerful approach for unsupervised object segmentation in videos.
• Refine and Represent: Region-to-Object Representation Learning
  25 Aug 2022 1 repository listed Syntology ran 0 of 5 samples · 5 unverified
  Recent works in self-supervised learning have demonstrated strong performance on scene-level dense prediction tasks by pretraining with object-centric or region-based correspondence objectives.
• Segmenting Moving Objects via an Object-Centric Layered Representation
  5 Jul 2022 1 repository listed Syntology ran 16 of 21 samples · 5 unverified
  The objective of this paper is a model that is able to discover, track and segment multiple moving objects in a video.
• Unsupervised Multi-object Segmentation Using Attention and Soft-argmax
  26 May 2022 1 repository listed
  We introduce a new architecture for unsupervised object-centric representation learning and multi-object detection and segmentation, which uses a translation-equivariant attention mechanism to predict the coordinates of…
• EM-driven unsupervised learning for efficient motion segmentation
  6 Jan 2022 1 repository listed
  The core idea of our work is to leverage the Expectation-Maximization (EM) framework in order to design in a well-founded manner a loss function and a training procedure of our motion segmentation neural network that…
• ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation
  19 Nov 2021 1 repository listed Syntology ran 1 of 8 samples · 7 unverified
  We benchmark a large set of recent unsupervised multi-object segmentation models on ClevrTex and find all state-of-the-art approaches fail to learn good representations in the textured setting, despite impressive…
• The Emergence of Objectness: Learning Zero-Shot Segmentation from Videos
  11 Nov 2021 1 repository listed
  Our model starts with two separate pathways: an appearance pathway that outputs feature-based region segmentation for a single image, and a motion pathway that outputs motion features for a pair of images.
• Object Segmentation Without Labels with Large-Scale Generative Models
  8 Jun 2020 1 repository listed
  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.
• Emergence of Object Segmentation in Perturbed Generative Models
  29 May 2019 1 repository listed
  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…
• Object Discovery with a Copy-Pasting GAN
  27 May 2019 1 repository listed Syntology ran 0 of 7 samples · 7 unverified
  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.
• Unsupervised Object Segmentation by Redrawing
  27 May 2019 1 repository listed
  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.

Syntology lines on 11 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.