mlsanityData to 14 Oct 2026

Few-Shot Referring Video Single- and Multi-Object Segmentation via Cross-Modal Affinity with Instance Sequence Matching

arXiv 2504.13710 ↗First posted 18 Apr 2025cs.CVcited by 5

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Abstract (arXiv)

Referring video object segmentation (RVOS) aims to segment objects in videos guided by natural language descriptions. We propose FS-RVOS, a Transformer-based model with two key components: a cross-modal affinity module and an instance sequence matching strategy, which extends FS-RVOS to multi-object segmentation (FS-RVMOS). Experiments show FS-RVOS and FS-RVMOS outperform state-of-the-art methods across diverse benchmarks, demonstrating superior robustness and accuracy.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 30 of its 50 references that are in the map. First posted on arXiv 18 Apr 2025.

Builds on

30 of 50 references.

References · 30

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2020End-to-End Object Detection with Transformerscited by 7,414
  5. 2016Feature Pyramid Networks for Object Detectioncited by 5,036
  6. 2020Deformable DETR: Deformable Transformers for End-to-End Object Detectioncited by 3,422
  7. 2016V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentationcited by 2,292
  8. 2020Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformerscited by 1,369
  9. 2021Per-Pixel Classification is Not All You Need for Semantic Segmentationcited by 1,152
  10. 2016Modeling Context in Referring Expressionscited by 1,063
  11. 2022DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETRcited by 573
  12. 2019PANet: Few-Shot Image Semantic Segmentation with Prototype Alignmentcited by 449
18 more
  1. 2017One-Shot Learning for Semantic Segmentationcited by 337
  2. 2020Prior Guided Feature Enrichment Network for Few-Shot Segmentationcited by 271
  3. 2023MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressionscited by 228
  4. 2020Prototype Mixture Models for Few-shot Semantic Segmentationcited by 190
  5. 2019Feature Weighting and Boosting for Few-Shot Segmentationcited by 189
  6. 2018Video Object Segmentation with Language Referring Expressionscited by 162
  7. 2021End-to-End Referring Video Object Segmentation with Multimodal Transformerscited by 135
  8. 2021Few-Shot Segmentation via Cycle-Consistent Transformercited by 133
  9. 2018Actor and Action Video Segmentation from a Sentencecited by 106
  10. 2023Referred by Multi-Modality: A Unified Temporal Transformer for Video Object Segmentationcited by 54
  11. 2022Towards Robust Referring Video Object Segmentation with Cyclic Relational Consensuscited by 50
  12. 2024Structure Matters: Tackling the Semantic Discrepancy in Diffusion Models for Image Inpaintingcited by 40
  13. 2024Bootstrapping Referring Multi-Object Trackingcited by 22
  14. 2022Modeling Motion with Multi-Modal Features for Text-Based Video Segmentationcited by 18
  15. 2022Weak-shot Semantic Segmentation via Dual Similarity Transfercited by 10
  16. 2021Weak-shot Semantic Segmentation by Transferring Semantic Affinity and Boundarycited by 7
  17. 2022CATrans: Context and Affinity Transformer for Few-Shot Segmentationcited by 7
  18. 2023Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samplescited by 6

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2025Multimodal Referring Segmentation: A Surveycited by 22
  2. 2026DORS: Dynamic Attention Routing for Diffusion-based Object Removal in Dense Scenescited by 1
  3. 2026AI-T2I: Aggregating-and-Isolating Cross-Attention to Diffusion Models for Text-to-Image Synthesiscited by 0
  4. 2026STEDiff: Strengthening Text Embedding for Text-to-Image Alignment in Diffusion Modelcited by 0
  5. 2026Rare Concept Generation via Counterfactual Inference in Diffusion Modelscited by 0