mlsanityData to 14 Oct 2026

CuVLER: Enhanced Unsupervised Object Discoveries through Exhaustive Self-Supervised Transformers

arXiv 2403.07700 ↗First posted 12 Mar 2024cs.CVcited by 16

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Abstract (arXiv)

In this paper, we introduce VoteCut, an innovative method for unsupervised object discovery that leverages feature representations from multiple self-supervised models. VoteCut employs normalized-cut based graph partitioning, clustering and a pixel voting approach. Additionally, We present CuVLER (Cut-Vote-and-LEaRn), a zero-shot model, trained using pseudo-labels, generated by VoteCut, and a novel soft target loss to refine segmentation accuracy. Through rigorous evaluations across multiple datasets and several unsupervised setups, our methods demonstrate significant improvements in comparison to previous state-of-the-art models. Our ablation studies further highlight the contributions of each component, revealing the robustness and efficacy of our approach. Collectively, VoteCut and CuVLER pave the way for future advancements in image segmentation.

Key facts. Cited by 16 papers in the map (data through 14 Oct 2026). Builds on 31 of its 41 references that are in the map. First posted on arXiv 12 Mar 2024.

Builds on

31 of 41 references.

References · 31

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19 more
  1. 2017Cascade R-CNN: Delving into High Quality Object Detectioncited by 1,276
  2. 2019LVIS: A Dataset for Large Vocabulary Instance Segmentationcited by 1,217
  3. 2021Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gaugescited by 1,167
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  14. 2023Cut and Learn for Unsupervised Object Detection and Instance Segmentationcited by 187
  15. 2022TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cutcited by 113
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 3; 2025: 7; 2026: 6.

16 papers.

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  1. 2024Image Segmentation in Foundation Model Era: A Surveycited by 35
  2. 2025Scene-Centric Unsupervised Panoptic Segmentationcited by 10
  3. 2024CutS3D: Cutting Semantics in 3D for 2D Unsupervised Instance Segmentationcited by 6
  4. 2025Beyond Single Images: Retrieval Self-Augmented Unsupervised Camouflaged Object Detectioncited by 5
  5. 2025FlowCut: Unsupervised Video Instance Segmentation via Temporal Mask Matchingcited by 2
  6. 2024MaDis-Stereo: Enhanced Stereo Matching via Distilled Masked Image Modelingcited by 1
  7. 2025Hierarchical Compact Clustering Attention (COCA) for Unsupervised Object-Centric Learningcited by 1
  8. 2026Scene-Centric Unsupervised Video Panoptic Segmentationcited by 1
  9. 2026Unlocking Diffusion Hierarchies: Adaptive Timestep Selection for Zero-Shot Segmentationcited by 1
  10. 2025Enhancing Object Discovery for Unsupervised Instance Segmentation and Object Detectioncited by 0
  11. 2025Unsupervised Instance Segmentation with Superpixelscited by 0
  12. 2025S2D: Sparse-To-Dense Keymask Distillation for Unsupervised Video Instance Segmentationcited by 0
4 more
  1. 2026Reference-based Category Discovery: Unsupervised Object Detection with Category Awarenesscited by 0
  2. 2026VVitCutLER: Towards Unsupervised Object Detection and Segmentation in Videoscited by 0
  3. 2026Diffuse2Seg: Diffusion Models Can Segment Anything Without Supervisioncited by 0
  4. 2026ProGuT: Label-Efficient Panoptic Segmentation for Forest Scenescited by 0