Latest Image Segmentation Research Papers

The newest Image Segmentation papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Image Segmentation so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.

Recent papers

• From Sparse to Dense: Label-Efficient Weakly Supervised Segmentation for Images and Videos
  J. Wang · Open MIND · Jan 1, 2027

  Obtaining high-quality annotated data has become a primary bottleneck for training deep learning models, particularly for dense prediction tasks like semantic segmentation and video salient object segmentation. The demand for meticulous, pi…

• What Drives Purchase Intention and Brand Loyalty in Affordable Luxury Fashion? Evidence from CoachConsumers
  Angela Audrey Sutanto, Dudi Anandya · Ubaya Repository (Universit... · Oct 1, 2026

  In the era of globalization and digitalization, Indonesia's luxury fashion industry has continued to grow, including the affordable luxury segment, creating a need for brands to understand the factors influencing consumers’ purchase intenti…

• RAGDNet: A Region-Adjacency Graph for Semantic Segmentation of Mechanical Drawings Using Graph Convolutional Networks
  Alexandre Monnier Weil, Nicolas Hili, Yves Ledru · Zenodo (CERN European Organ... · Aug 1, 2026
• RAGDNet: A Region-Adjacency Graph for Semantic Segmentation of Mechanical Drawings Using Graph Convolutional Networks
  Alexandre Monnier Weil, Nicolas Hili, Yves Ledru · Zenodo (CERN European Organ... · Aug 1, 2026
• SPDCN: Strip-based Deformable Convolutional Network for Steel Surface Defect Segmentation
  Zhongming Liu, Bingbing Jiang, Guangxin Wan, Xiang Zou · arXiv · Jul 23, 2026

  Steel surface defect segmentation is critical for industrial quality inspection, yet existing methods struggle with elongated, anisotropic defects such as cracks and scratches due to the isotropic receptive fields of standard convolutions a…

• DINOde: Continuous Vision-Text Alignment for Open-Vocabulary Semantic Segmentation
  Sung-Hoon Yoon, Hoyong Kwon, Changgyoon Oh, Kuk-Jin Yoon · arXiv · Jul 23, 2026

  Open-vocabulary semantic segmentation (OVSS) leverages textual semantics to segment objects beyond predefined categories. While the self-supervised model DINOv3 provides strong structured visual representations, its lack of native textual a…

• ASTRA-Net: Anatomy-Specific Transfer and Representation Alignment for Drug-Induced Sleep Endoscopy Segmentation
  Suhua Sun, Yuqiao Wang, Sheng Liu, Rui Fan et al. · arXiv · Jul 23, 2026

  Quantitative drug-induced sleep endoscopy (DISE) requires reliable airway boundaries at specific anatomical levels. Pixel-level DISE annotations are scarce, and manual contouring limits the scalability of quantitative assessment. To address…

• T-STAR: A Large-Scale Benchmark for Spatio-Temporal Panoptic Scene Graph Generation in Satellite Video
  Linlin Wang, Xue Yang, Zhihuang Zhou, Zhenyu Zhong et al. · arXiv · Jul 23, 2026

  Structured understanding of satellite video is essential for advancing dynamic geospatial scene analysis from low-level perception to high-level cognition. To move beyond object-centric perception, this paper introduces spatio-temporal pano…

• Toward Reliable RGB-D Semantic Segmentation: Handling Missing Modalities via Condition Dropout
  Xuchen Zhu, Yajuan Wei, Shuang Hao, Jiwei Jiang et al. · arXiv · Jul 22, 2026

  RGB-D semantic segmentation has achieved remarkable progress, yet most models assume that RGB and depth are always available. In practice, failures or occlusions of surveillance sensors often remove one modality. Although RGB or depth alone…

• Binary image acquisition and texture parameter calculation of asphalt pavement based on a U-Net model
  Fengwei An, Haoran Jiang, Yulong Zhao, Lei Fang et al. · PLoS ONE · Jul 22, 2026

  Current methods for detecting and evaluating pavement skid resistance vary widely, yet each has its own scope of applicability and inherent limitations. Therefore, this paper proposes a method based on U-Net model segmentation to obtain bin…

• A Hybrid Self-Supervised Denoising and Attention-Guided Segmentation Framework for Robust Medical Image Analysis
  Swarna N · IJARCCE · Jul 21, 2026

  Medical image analysis plays a fundamental role in modern clinical diagnosis and treatment planning.However, the presence of acquisition noise, low contrast, and indistinct anatomical boundaries often degrades image quality, thereby reducin…

• Automated and Scalable SEM Image Analysis of Perovskite Solar Cell Materials via a Deep Segmentation Framework
  Lin Wang, Tianxiang Hu, Jianguo Pan, Hao Zhang et al. · npj Computational Materials · Jul 20, 2026

  Abstract Scanning Electron Microscopy (SEM) is indispensable for characterizing perovskite thin-film microstructure. However, current analysis remains largely manual, limiting throughput and consistency. Here, we present PerovSegNet, an aut…

• Automated morphometric segmentation analysis of hand X-ray image using deep learning network
  YiYang Zhang, Zhukai Zhuang, Pengli Yu, Yachong Guo et al. · BMC Medical Imaging · Jul 20, 2026
• Screening glioma and glioblastoma brain tumors using dual deep learning algorithm incorporated correlative GAN and BrainNet through the probability segmentation
  L. Mohana Sundari, T. Senthil Kumar, M. Rajkumar, D Karthikeyan · Scientific Reports · Jul 20, 2026

  The earlier identification of the tumors in human brain can improve the life time of the affected patients. Mainly, Glioma and Glioblastoma are the primary type of brain tumors where the survival rate of the patient is low and hence it’s ea…

• Compressive capacity of concrete dry joints across shotcrete, extrusion, and particle-bed additive manufacturing with robotic subtractive finishing
  Abtin Baghdadi, Robin Doerrie, Harald Kloft · Materials and Structures · Jul 20, 2026

  Abstract Additively manufactured (AM) concrete segments often require reliable, repeatable dry-joint interfaces, yet segmentation quality and dimensional accuracy remain challenging. This study evaluates dry joints produced by robotic subtr…

• Bidirectional cross-view learning with dynamic region selection for semi-supervised medical image segmentation
  Jiangxiong Fang, Hao Luo, Haihuai Zeng, Jie Jin et al. · Complex & Intelligent Systems · Jul 18, 2026

  Semi-supervised medical image segmentation aims to alleviate the heavy reliance on dense annotations while preserving high segmentation accuracy, yet it remains challenging due to unreliable pseudo-labels and insufficient utilization of unl…

• Diagnostic performance of an artificial intelligence algorithm for detecting pneumoperitoneum on abdominal CT scans
  Yuwan Hu, Zhigang Sun, Haoyu Li, Shuya Gao et al. · Insights into Imaging · Jul 18, 2026

  Abstract Objectives This study aims to evaluate the diagnostic performance of an artificial intelligence (AI) algorithm for detection, segmentation, and volumetric quantification of pneumoperitoneum on abdominal CT scans. Materials and meth…

• Context-Adaptive Neurolex Segmentation Algorithm for Machine Learning NLP Systems
  Kesava Rao Alla, Gunasekar Thangarasu, Kayalvizhi Subramanian, Mohamed Ubaidullah · International Journal of Dr... · Jul 18, 2026

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• AI‑Powered Real-Time Structural Health Monitoring Using Crack Detection, Vegetation Segmentation, and Depth Analysis
  Rijja H, Rohith Varshighan S, Sreehari Veeramachaneni, Shiv Nadar Institution of Eminence et al. · e-Journal of Nondestructive... · Jul 17, 2026

  Context / Content: Civil infrastructure and heritage structures deteriorate with time due to environmental exposure, material aging, moisture ingress, pollution, and biological growth. Traditional inspection relies heavily on manual assessm…

• Mamba-SDA: integrating state-space models with spatial-depth attention for multimodal remote sensing image segmentation
  Xiandai Cui · Journal of Applied Remote S... · Jul 17, 2026

  The precision in classifying multimodal remote sensing data plays a pivotal role in advancing the accuracy of land cover mapping and bolstering capabilities for observing environmental dynamics. Although current techniques offer distinct ad…

• CRISP: Constrained Refinement via Iterative Squeezing Process for Robust Medical Image Segmentation under Domain Shift
  Yizhou Fang, Pujin Cheng, Yixiang Liu, Xiaoying Tang et al. · arXiv · Jul 16, 2026

  Distribution shift in medical imaging remains a central bottleneck for the clinical translation of medical AI. Failure to address it can lead to severe performance degradation in unseen environments and exacerbate health inequities. Existin…

• Weakly-Supervised RGB-D Salient Object Detection via SAM-driven Pseudo Annotation and State Space Interaction-based Diffusion
  Wenqi Si, Gongyang Li, Shixiang Shi, Weisi Lin · arXiv · Jul 16, 2026

  Weakly-supervised RGB-D Salient Object Detection (SOD) is explored to reduce the heavy burden of pixel-level annotations. But scribble annotations lack the structure and details of objects, resulting in inaccurate saliency maps. In this pap…

• Stitch-Inferencer: Enhance Endoscopic Video Segmentation and Tracking via Panoramic Reconstruction
  Shunsuke Kikuchi, Atsushi Kouno, Hiroki Matsuzaki · arXiv · Jul 16, 2026

  Surgical video understanding is fundamental to navigation systems. Endoscopic perception is often hindered by a limited field-of-view and frequent instrument occlusions, making spatio-temporal context essential for robust inference. These c…

• Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels
  Michael Halstead, Esra Guclu, Mohamed Farag, Enrico Pallotta et al. · arXiv · Jul 16, 2026

  In this manuscript we release two datasets for visual sensing of tomato plants grown in commercial-like settings and acquired using a robot. The first is BUTom21 which consists of still images and manual annotations. The second is BUTom-ST2…

• Disentangling color bias and semantic consistency for single-source domain generalization in fundus multi-lesion segmentation
  Jie Liu, H Y Liu, Puzhen Sun, Xiaolan Wang et al. · Biomedical Signal Processin... · Jul 16, 2026
• A Robust Visual Grasping Method for Robots in Cluttered and Stacked Scenes
  Zhiqiang Gao, Mengqi Li, Huihui Bai, Jinze Li et al. · Sensors · Jul 16, 2026

  In complex backgrounds and under severe occlusions, the accuracy of vision-based robotic grasping pose estimation decreases significantly, further making objects difficult to manipulate and grasp. This paper proposes an iterative closed-loo…

• Point Tracking in Surgery--The 2025 Surgical Tattoos in Infrared Challenge (STIRC2025)
  Adam Schmidt, Mert Asim Karaoglu, Zijian Wu, Jiaming Zhang et al. · arXiv · Jul 14, 2026

  Point tracking in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning, and subtask autonomy. This paper introduces the 2025 itera…

• UniMedSeg: Unified In-Context Learning for Multi-Paradigm 2D/3D Medical Image Segmentation
  Yunzhou Li, Jiesi Hu, Yanwu Yang, Hanyang Peng et al. · arXiv · Jul 14, 2026

  Medical image segmentation foundation models are expected to generalize across diverse clinical scenarios, yet existing universal methods remain fragmented by prompt paradigms and spatial dimensions. Visual in-context learning, interactive …

• LARAD: Layout-Aware Road Anomaly Detection via Spatial-Logic Reasoning
  Shiyi Mu, Xujie Chen, Shugong Xu · arXiv · Jul 14, 2026

  Accurate open-world obstacle detection is critical for autonomous driving. Current anomaly segmentation methods suffer from a fundamental blind spot: they over-rely on texture novelty to identify out-of-distribution (OoD) objects while igno…

• Deep learning-based segmentation and subtype prediction of renal cell carcinoma on contrast-enhanced CT
  Xiaoliang Chen, Yingwei Xie, Zehai Huang, Bihong Xu et al. · npj Precision Oncology · Jul 14, 2026

  Accurate preoperative discrimination of renal cell carcinoma (RCC) subtypes is critical for treatment stratification. We aimed to develop and validate an automated deep learning system for simultaneous tumor segmentation and histopathologic…