mlsanityData to 14 Oct 2026

Adaptive Low Rank Adaptation of Segment Anything to Salient Object Detection

arXiv 2308.05426 ↗First posted 10 Aug 2023cs.CVcited by 7

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Abstract (arXiv)

Foundation models, such as OpenAI's GPT-3 and GPT-4, Meta's LLaMA, and Google's PaLM2, have revolutionized the field of artificial intelligence. A notable paradigm shift has been the advent of the Segment Anything Model (SAM), which has exhibited a remarkable capability to segment real-world objects, trained on 1 billion masks and 11 million images. Although SAM excels in general object segmentation, it lacks the intrinsic ability to detect salient objects, resulting in suboptimal performance in this domain. To address this challenge, we present the Segment Salient Object Model (SSOM), an innovative approach that adaptively fine-tunes SAM for salient object detection by harnessing the low-rank structure inherent in deep learning. Comprehensive qualitative and quantitative evaluations across five challenging RGB benchmark datasets demonstrate the superior performance of our approach, surpassing state-of-the-art methods.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 29 of its 42 references that are in the map. First posted on arXiv 10 Aug 2023.

Builds on

29 of 42 references.

References · 29

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17 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 3; 2025: 1; 2026: 2.

7 papers.

  1. 2024SSFam: Scribble Supervised Salient Object Detection Familycited by 6
  2. 2026EgoHandICL: Egocentric 3D Hand Reconstruction with In-Context Learningcited by 3
  3. 2023SqueezeSAM: User friendly mobile interactive segmentationcited by 2
  4. 2024Segment Any Object Model (SAOM): Real-to-Simulation Fine-Tuning Strategy for Multi-Class Multi-Instance Segmentationcited by 2
  5. 2024Enhancing Aspect-based Sentiment Analysis in Tourism Using Large Language Models and Positional Informationcited by 1
  6. 2025Towards Size-invariant Salient Object Detection: A Generic Evaluation and Optimization Approachcited by 0
  7. 2026Global-Local Feature Decoding with Adapter-Guided SAMv2 for Salient Object Detectioncited by 0